load("df.Rdata")

attributes(df)$label <- c("This is a test", "HERE BE ITEM STEM")

codebook::codebook(df)

## Warning in codebook::codebook(df): The variables session, created, ended
## have to be defined for automatic survey repetition detection to work. Set
## to no repetition by default.

knitr::asis_output(survey_overview)

Items

knitr::asis_output(paste0(scales_items, sep = "\n\n\n", collapse = "\n\n\n"))

id

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

## 1165  unique, categorical values, so not shown.

knitr::opts_chunk$set(fig.height = old_height)

0 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	ordered	missing	complete	n	n_unique	top_counts	V1	V2	V3	V4	V5	V6	V7	V8	V9	V10	V11	V12	V13	V14	V15	V16	V17	V18	V19	V20	V21	V22	V23	V24	V25	V26	V27	V28	V29	V30	V31	V32	V33	V34	V35	V36	V37	V38	V39	V40	V41	V42	V43	V44	V45	V46	V47	V48	V49	V50	V51	V52	V53	V54	V55	V56	V57	V58	V59	V60	V61	V62	V63	V64	V65	V66	V67	V68	V69	V70	V71	V72	V73	V74	V75	V76	V77	V78	V79	V80	V81	V82	V83	V84	V85	V86	V87	V88	V89	V90	V91	V92	V93	V94	V95	V96	V97	V98	V99	V100	V101	V102	V103	V104	V105	V106	V107	V108	V109	V110	V111	V112	V113	V114	V115	V116	V117	V118	V119	V120	V121	V122	V123	V124	V125	V126	V127	V128	V129	V130	V131	V132	V133	V134	V135	V136	V137	V138	V139	V140	V141	V142	V143	V144	V145	V146	V147	V148	V149	V150	V151	V152	V153	V154	V155	V156	V157	V158	V159	V160	V161	V162	V163	V164	V165	V166	V167	V168	V169	V170	V171	V172	V173	V174	V175	V176	V177	V178	V179	V180	V181	V182	V183	V184	V185	V186	V187	V188	V189	V190	V191	V192	V193	V194	V195	V196	V197	V198	V199	V200	V201	V202	V203	V204	V205	V206	V207	V208	V209	V210	V211	V212	V213	V214	V215	V216	V217	V218	V219	V220	V221	V222	V223	V224	V225	V226	V227	V228	V229	V230	V231	V232	V233	V234	V235	V236	V237	V238	V239	V240	V241	V242	V243	V244	V245	V246	V247	V248	V249	V250	V251	V252	V253	V254	V255	V256	V257	V258	V259	V260	V261	V262	V263	V264	V265	V266	V267	V268	V269	V270	V271	V272	V273	V274	V275	V276	V277	V278	V279	V280	V281	V282	V283	V284	V285	V286	V287	V288	V289	V290	V291	V292	V293	V294	V295	V296	V297	V298	V299	V300	V301	V302	V303	V304	V305	V306	V307	V308	V309	V310	V311	V312	V313	V314	V315	V316	V317	V318	V319	V320	V321	V322	V323	V324	V325	V326	V327	V328	V329	V330	V331	V332	V333	V334	V335	V336	V337	V338	V339	V340	V341	V342	V343	V344	V345	V346	V347	V348	V349	V350	V351	V352	V353	V354	V355	V356	V357	V358	V359	V360	V361	V362	V363	V364	V365	V366	V367	V368	V369	V370	V371	V372	V373	V374	V375	V376	V377	V378	V379	V380	V381	V382	V383	V384	V385	V386	V387	V388	V389	V390	V391	V392	V393	V394	V395	V396	V397	V398	V399	V400	V401	V402	V403	V404	V405	V406	V407	V408	V409	V410	V411	V412	V413	V414	V415	V416	V417	V418	V419	V420	V421	V422	V423	V424	V425	V426	V427	V428	V429	V430	V431	V432	V433	V434	V435	V436	V437	V438	V439	V440	V441	V442	V443	V444	V445	V446	V447	V448	V449	V450	V451	V452	V453	V454	V455	V456	V457	V458	V459	V460	V461	V462	V463	V464	V465	V466	V467	V468	V469	V470	V471	V472	V473	V474	V475	V476	V477	V478	V479	V480	V481	V482	V483	V484	V485	V486	V487	V488	V489	V490	V491	V492	V493	V494	V495	V496	V497	V498	V499	V500	V501	V502	V503	V504	V505	V506	V507	V508	V509	V510	V511	V512	V513	V514	V515	V516	V517	V518	V519	V520	V521	V522	V523	V524	V525	V526	V527	V528	V529	V530	V531	V532	V533	V534	V535	V536	V537	V538	V539	V540	V541	V542	V543	V544	V545	V546	V547	V548	V549	V550	V551	V552	V553	V554	V555	V556	V557	V558	V559	V560	V561	V562	V563	V564	V565	V566	V567	V568	V569	V570	V571	V572	V573	V574	V575	V576	V577	V578	V579	V580	V581	V582	V583	V584	V585	V586	V587	V588	V589	V590	V591	V592	V593	V594	V595	V596	V597	V598	V599	V600	V601	V602	V603	V604	V605	V606	V607	V608	V609	V610	V611	V612	V613	V614	V615	V616	V617	V618	V619	V620	V621	V622	V623	V624	V625	V626	V627	V628	V629	V630	V631	V632	V633	V634	V635	V636	V637	V638	V639	V640	V641	V642	V643	V644	V645	V646	V647	V648	V649	V650	V651	V652	V653	V654	V655	V656	V657	V658	V659	V660	V661	V662	V663	V664	V665	V666	V667	V668	V669	V670	V671	V672	V673	V674	V675	V676	V677	V678	V679	V680	V681	V682	V683	V684	V685	V686	V687	V688	V689	V690	V691	V692	V693	V694	V695	V696	V697	V698	V699	V700	V701	V702	V703	V704	V705	V706	V707	V708	V709	V710	V711	V712	V713	V714	V715	V716	V717	V718	V719	V720	V721	V722	V723	V724	V725	V726	V727	V728	V729	V730	V731	V732	V733	V734	V735	V736	V737	V738	V739	V740	V741	V742	V743	V744	V745	V746	V747	V748	V749	V750	V751	V752	V753	V754	V755	V756	V757	V758	V759	V760	V761	V762	V763	V764	V765	V766	V767	V768	V769	V770	V771	V772	V773	V774	V775	V776	V777	V778	V779	V780	V781	V782	V783	V784	V785	V786	V787	V788	V789	V790	V791	V792	V793	V794	V795	V796	V797	V798	V799	V800	V801	V802	V803	V804	V805	V806	V807	V808	V809	V810	V811	V812	V813	V814	V815	V816	V817	V818	V819	V820	V821	V822	V823	V824	V825	V826	V827	V828	V829	V830	V831	V832	V833	V834	V835	V836	V837	V838	V839	V840	V841	V842	V843	V844	V845	V846	V847	V848	V849	V850	V851	V852	V853	V854	V855	V856	V857	V858	V859	V860	V861	V862	V863	V864	V865	V866	V867	V868	V869	V870	V871	V872	V873	V874	V875	V876	V877	V878	V879	V880	V881	V882	V883	V884	V885	V886	V887	V888	V889	V890	V891	V892	V893	V894	V895	V896	V897	V898	V899	V900	V901	V902	V903	V904	V905	V906	V907	V908	V909	V910	V911	V912	V913	V914	V915	V916	V917	V918	V919	V920	V921	V922	V923	V924	V925	V926	V927	V928	V929	V930	V931	V932	V933	V934	V935	V936	V937	V938	V939	V940	V941	V942	V943	V944	V945	V946	V947	V948	V949	V950	V951	V952	V953	V954	V955	V956	V957	V958	V959	V960	V961	V962	V963	V964	V965	V966	V967	V968	V969	V970	V971	V972	V973	V974	V975	V976	V977	V978	V979	V980	V981	V982	V983	V984	V985	V986	V987	V988	V989	V990	V991	V992	V993	V994	V995	V996	V997	V998	V999	V1000	V1001	V1002	V1003	V1004	V1005	V1006	V1007	V1008	V1009	V1010	V1011	V1012	V1013	V1014	V1015	V1016	V1017	V1018	V1019	V1020	V1021	V1022	V1023	V1024	V1025	V1026	V1027	V1028	V1029	V1030	V1031	V1032	V1033	V1034	V1035	V1036	V1037	V1038	V1039	V1040	V1041	V1042	V1043	V1044	V1045	V1046	V1047	V1048	V1049	V1050	V1051	V1052	V1053	V1054	V1055	V1056	V1057	V1058	V1059	V1060	V1061	V1062	V1063	V1064	V1065	V1066	V1067	V1068	V1069	V1070	V1071	V1072	V1073	V1074	V1075	V1076	V1077	V1078	V1079	V1080	V1081	V1082	V1083	V1084	V1085	V1086	V1087	V1088	V1089	V1090	V1091	V1092	V1093	V1094	V1095	V1096	V1097	V1098	V1099	V1100	V1101	V1102	V1103	V1104	V1105	V1106	V1107	V1108	V1109	V1110	V1111	V1112	V1113	V1114	V1115	V1116	V1117	V1118	V1119	V1120	V1121	V1122	V1123	V1124	V1125	V1126	V1127	V1128	V1129	V1130	V1131	V1132	V1133	V1134	V1135	V1136	V1137	V1138	V1139	V1140	V1141	V1142	V1143	V1144	V1145	V1146	V1147	V1148	V1149	V1150	V1151	V1152	V1153	V1154	V1155	V1156	V1157	V1158	V1159	V1160	V1161	V1162	V1163	V1164	V1165
id	factor	FALSE	0	1165	1165	1165	1-1: 1, 1-1: 1, 1-1: 1, 1-1: 1	1-1-0004	1-1-0011	1-1-0012	1-1-0019	1-1-0020	1-1-0022	1-1-0040	1-1-0041	1-1-0055	1-1-0056	1-1-0060	1-1-0069	1-1-0084	1-1-0092	1-1-0103	1-1-0114	1-1-0115	1-1-0118	1-1-0123	1-1-0124	1-1-0139	1-1-0144	1-1-0158	1-1-0173	1-1-0174	1-1-0182	1-1-0186	1-1-0188	1-1-0194	1-1-0197	1-1-0202	1-1-0215	1-1-0219	1-1-0220	1-1-0224	1-1-0225	1-1-0228	1-1-0230	1-1-0231	1-1-0251	1-1-0260	1-1-0272	1-1-0275	1-1-0288	1-1-0292	1-1-0296	1-1-0301	1-1-0309	1-1-0319	1-1-0320	1-1-0330	1-1-0333	1-1-0338	1-1-0345	1-1-0350	1-1-0355	1-1-0357	1-1-0361	1-1-0364	1-1-0372	1-1-0376	1-1-0383	1-1-0387	1-1-0399	1-1-0401	1-1-0404	1-1-0409	1-1-0411	1-1-0415	1-1-0416	1-1-0426	1-1-0430	1-1-0432	1-1-0442	1-1-0453	1-1-0479	1-1-0505	1-1-0506	1-1-0509	1-1-0510	1-1-0515	1-1-0517	1-1-0521	1-1-0530	1-1-0546	1-1-0550	1-1-0572	1-1-0580	1-1-0595	1-1-0606	1-1-0610	1-1-0618	1-1-0639	1-1-0652	1-1-0657	1-1-0681	1-1-0688	1-1-0714	1-1-0721	1-1-0725	1-1-0727	1-1-0738	1-1-0752	1-1-0774	1-1-0792	1-1-0794	1-1-0797	1-1-0801	1-1-0807	1-1-0809	1-1-0812	1-1-0820	1-1-0833	1-1-0846	1-1-0856	1-1-0860	1-1-0870	1-1-0879	1-1-0880	1-1-0881	1-1-0893	1-1-0900	1-1-0902	1-1-0906	1-1-0917	1-1-0940	1-1-0941	1-1-0960	1-1-0966	1-1-0969	1-1-0988	1-1-0991	1-1-1010	1-1-1012	1-1-1015	1-1-1016	1-1-1017	1-1-1022	1-1-1027	1-1-1028	1-1-1035	1-1-1048	1-1-1064	1-1-1065	1-1-1073	1-1-1083	1-1-1086	1-1-1093	1-1-1097	1-1-1100	1-1-1108	1-1-1112	1-1-1116	1-1-1126	1-1-1134	1-1-1163	1-1-1166	1-2-0005	1-2-0032	1-2-0050	1-2-0077	1-2-0085	1-2-0096	1-2-0126	1-2-0159	1-2-0181	1-2-0185	1-2-0198	1-2-0217	1-2-0257	1-2-0261	1-2-0264	1-2-0278	1-2-0285	1-2-0290	1-2-0304	1-2-0326	1-2-0352	1-2-0367	1-2-0374	1-2-0390	1-2-0408	1-2-0413	1-2-0421	1-2-0424	1-2-0425	1-2-0428	1-2-0447	1-2-0448	1-2-0450	1-2-0492	1-2-0497	1-2-0507	1-2-0518	1-2-0522	1-2-0524	1-2-0535	1-2-0537	1-2-0544	1-2-0545	1-2-0571	1-2-0574	1-2-0575	1-2-0581	1-2-0597	1-2-0613	1-2-0617	1-2-0631	1-2-0661	1-2-0678	1-2-0679	1-2-0685	1-2-0692	1-2-0700	1-2-0704	1-2-0706	1-2-0739	1-2-0743	1-2-0744	1-2-0751	1-2-0773	1-2-0778	1-2-0783	1-2-0804	1-2-0826	1-2-0828	1-2-0834	1-2-0837	1-2-0840	1-2-0852	1-2-0853	1-2-0857	1-2-0863	1-2-0865	1-2-0872	1-2-0877	1-2-0908	1-2-0936	1-2-0938	1-2-0950	1-2-0954	1-2-0979	1-2-0992	1-2-0993	1-2-0998	1-2-1029	1-2-1041	1-2-1046	1-2-1059	1-2-1077	1-2-1098	1-2-1135	1-2-1154	1-2-1160	1-2-1168	1-2-1169	2-1-0002	2-1-0030	2-1-0071	2-1-0090	2-1-0099	2-1-0101	2-1-0129	2-1-0137	2-1-0168	2-1-0176	2-1-0183	2-1-0187	2-1-0195	2-1-0206	2-1-0222	2-1-0232	2-1-0266	2-1-0281	2-1-0303	2-1-0306	2-1-0307	2-1-0318	2-1-0334	2-1-0341	2-1-0343	2-1-0393	2-1-0405	2-1-0410	2-1-0414	2-1-0452	2-1-0486	2-1-0491	2-1-0494	2-1-0495	2-1-0513	2-1-0520	2-1-0536	2-1-0547	2-1-0552	2-1-0564	2-1-0567	2-1-0607	2-1-0611	2-1-0616	2-1-0619	2-1-0645	2-1-0654	2-1-0660	2-1-0691	2-1-0698	2-1-0709	2-1-0737	2-1-0741	2-1-0765	2-1-0772	2-1-0793	2-1-0800	2-1-0805	2-1-0821	2-1-0822	2-1-0838	2-1-0858	2-1-0871	2-1-0891	2-1-0905	2-1-0907	2-1-0915	2-1-0920	2-1-0931	2-1-0937	2-1-0942	2-1-0948	2-1-0953	2-1-0971	2-1-0981	2-1-0982	2-1-0985	2-1-1005	2-1-1054	2-1-1069	2-1-1074	2-1-1078	2-1-1079	2-1-1081	2-1-1088	2-1-1089	2-1-1091	2-1-1109	2-1-1118	2-1-1120	2-1-1151	2-1-1155	2-1-1156	2-1-1173	2-1-1184	2-1-1185	2-2-0003	2-2-0021	2-2-0026	2-2-0034	2-2-0035	2-2-0043	2-2-0049	2-2-0057	2-2-0070	2-2-0072	2-2-0073	2-2-0081	2-2-0106	2-2-0108	2-2-0110	2-2-0116	2-2-0120	2-2-0122	2-2-0130	2-2-0135	2-2-0143	2-2-0148	2-2-0152	2-2-0153	2-2-0156	2-2-0163	2-2-0167	2-2-0169	2-2-0170	2-2-0175	2-2-0179	2-2-0189	2-2-0190	2-2-0192	2-2-0214	2-2-0234	2-2-0239	2-2-0244	2-2-0246	2-2-0255	2-2-0256	2-2-0282	2-2-0283	2-2-0294	2-2-0299	2-2-0314	2-2-0327	2-2-0332	2-2-0363	2-2-0368	2-2-0369	2-2-0373	2-2-0377	2-2-0384	2-2-0395	2-2-0398	2-2-0402	2-2-0423	2-2-0437	2-2-0454	2-2-0469	2-2-0471	2-2-0474	2-2-0476	2-2-0478	2-2-0481	2-2-0487	2-2-0532	2-2-0554	2-2-0558	2-2-0560	2-2-0561	2-2-0579	2-2-0583	2-2-0586	2-2-0590	2-2-0599	2-2-0612	2-2-0620	2-2-0621	2-2-0628	2-2-0630	2-2-0642	2-2-0655	2-2-0658	2-2-0663	2-2-0677	2-2-0682	2-2-0686	2-2-0695	2-2-0697	2-2-0701	2-2-0705	2-2-0710	2-2-0722	2-2-0730	2-2-0745	2-2-0750	2-2-0770	2-2-0782	2-2-0791	2-2-0823	2-2-0827	2-2-0830	2-2-0831	2-2-0836	2-2-0842	2-2-0843	2-2-0847	2-2-0864	2-2-0909	2-2-0924	2-2-0930	2-2-0932	2-2-0933	2-2-0934	2-2-0939	2-2-0962	2-2-0967	2-2-0972	2-2-0980	2-2-0995	2-2-0997	2-2-1007	2-2-1014	2-2-1047	2-2-1055	2-2-1057	2-2-1063	2-2-1067	2-2-1082	2-2-1101	2-2-1105	2-2-1110	2-2-1122	2-2-1139	2-2-1142	2-2-1143	2-2-1162	2-2-1178	2-2-1179	2-2-1180	2-2-1181	3-3-0008	3-3-0017	3-3-0037	3-3-0068	3-3-0100	3-3-0125	3-3-0138	3-3-0142	3-3-0166	3-3-0199	3-3-0204	3-3-0211	3-3-0229	3-3-0249	3-3-0254	3-3-0262	3-3-0295	3-3-0321	3-3-0325	3-3-0342	3-3-0346	3-3-0366	3-3-0378	3-3-0406	3-3-0412	3-3-0419	3-3-0445	3-3-0477	3-3-0485	3-3-0508	3-3-0526	3-3-0528	3-3-0533	3-3-0553	3-3-0565	3-3-0576	3-3-0585	3-3-0587	3-3-0593	3-3-0605	3-3-0609	3-3-0651	3-3-0662	3-3-0676	3-3-0699	3-3-0702	3-3-0711	3-3-0718	3-3-0719	3-3-0729	3-3-0754	3-3-0756	3-3-0757	3-3-0768	3-3-0781	3-3-0785	3-3-0790	3-3-0811	3-3-0825	3-3-0835	3-3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if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

intervention

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

81 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	ordered	missing	complete	n	n_unique	top_counts	V1	V2
intervention	factor	FALSE	81	1084	1165	2	1: 581, 0: 503, NA: 81	0	1

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

group

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

## 59  unique, categorical values, so not shown.

knitr::opts_chunk$set(fig.height = old_height)

81 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	ordered	missing	complete	n	n_unique	top_counts	V1	V2	V3	V4	V5	V6	V7	V8	V9	V10	V11	V12	V13	V14	V15	V16	V17	V18	V19	V20	V21	V22	V23	V24	V25	V26	V27	V28	V29	V30	V31	V32	V33	V34	V35	V36	V37	V38	V39	V40	V41	V42	V43	V44	V45	V46	V47	V48	V49	V50	V51	V52	V53	V54	V55	V56	V57	V58	V59
group	factor	FALSE	81	1084	1165	59	NA: 81, LHS: 27, LHS: 26, LHS: 26	14KP2A	14KP2B	14KP2C	14KP2D	14RYP2	14TP2	15PTA	15PTE	15RYP	DATP13SAG	DATP13SBG	DATP14SAG	DATP14SBG	DATP14SCG	DB14S1B	DP14L2A	DP14S1A	DP14S1B	DP14S2A	DP14S3A	HVIP14SAC	LHK15AV	LHK15CR	LHK15PK	LHS14CR	LHS14DR	LHS14KT	LHS14PKC	LHS15AR	LHS15AV	LHS15BR	LHS15BV	LHS15CR	LHS15CV	LHS15DR	LHS15DV	LHS15EV	LHS15KT	LHS15PKB	LHS15PKC	LKH15AV	MERP13SAG	MERP13SCG	MERP13SDG	MERP14SAG	MERP14SBG	MERP14SCG	MERP14SDG	MERP14SEG	MP14SA	MP14SB	MP14SD	MP14SE	MP14SF	MP14SG	MP14SH	RKOP14SBC	RKOP14SCC	RKOP15SBC

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

school

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

81 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	ordered	missing	complete	n	n_unique	top_counts	V1	V2	V3	V4	V5
school	factor	FALSE	81	1084	1165	5	1: 293, 4: 288, 2: 223, 5: 148	1	2	3	4	5

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

girl

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

81 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	ordered	missing	complete	n	n_unique	top_counts	V1	V2
girl	factor	FALSE	81	1084	1165	2	gir: 613, boy: 471, NA: 81	girl	boy

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

track

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

81 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	ordered	missing	complete	n	n_unique	top_counts	V1	V2	V3	V4	V5
track	factor	FALSE	81	1084	1165	5	Nur: 402, BA: 282, HRC: 213, IT: 163	Other	IT	BA	HRC	Nur

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

big5agreeableness_01_T1

Kys0155.1: … sympaattinen ja ystävällinen

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

104 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
big5agreeableness_01_T1	Kys0155.1: … sympaattinen ja ystävällinen	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	104	1061	1165	7	7: 315, 6: 292, 5: 204, 4: 166	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

big5agrReverseCoded_02_T1

Kys0150.1: … arvostelen asioita tai ihmisiä usein ja joudun helposti riitoihin

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

101 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
big5agrReverseCoded_02_T1	Kys0150.1: … arvostelen asioita tai ihmisiä usein ja joudun helposti riitoihin	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	101	1064	1165	7	7: 321, 6: 229, 4: 204, 5: 133	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

big5conscientiousness_01_T1

Kys0151.1: … luotettava ja saan tehtyä ne asiat, jotka lupaan tehdä

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

106 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
big5conscientiousness_01_T1	Kys0151.1: … luotettava ja saan tehtyä ne asiat, jotka lupaan tehdä	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	106	1059	1165	7	6: 314, 7: 273, 5: 204, 4: 161	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

big5consReverseCoded_02_T1

Kys0156.1: … huolimaton ja minun on vaikeaa järjestellä asioita

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

100 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
big5consReverseCoded_02_T1	Kys0156.1: … huolimaton ja minun on vaikeaa järjestellä asioita	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	100	1065	1165	7	4: 244, 6: 211, 7: 208, 3: 128	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

big5extraversion_01_T1

Kys0149.1: … ulospäin suuntautunut, innostunut asioista

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

102 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
big5extraversion_01_T1	Kys0149.1: … ulospäin suuntautunut, innostunut asioista	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	102	1063	1165	7	7: 245, 6: 221, 4: 218, 5: 184	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

big5extReverseCoded_02_T1

Kys0154.1: … varautunut (varovainen uusien ihmisten seurassa) ja hiljainen

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

103 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
big5extReverseCoded_02_T1	Kys0154.1: … varautunut (varovainen uusien ihmisten seurassa) ja hiljainen	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	103	1062	1165	7	4: 229, 3: 159, 6: 148, 7: 138	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

big5neuroticism_01_T1

Kys0152.1: … välillä ahdistunut ja hermostun helposti

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

101 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
big5neuroticism_01_T1	Kys0152.1: … välillä ahdistunut ja hermostun helposti	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	101	1064	1165	7	4: 222, 2: 167, 5: 166, 7: 151	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

big5neurReverseCoded_02_T1

Kys0157.1: … tyyni ja tasapainoinen

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

104 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
big5neurReverseCoded_02_T1	Kys0157.1: … tyyni ja tasapainoinen	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	104	1061	1165	7	4: 321, 3: 198, 2: 151, 1: 139	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

big5openness_01_T1

Kys0153.1: … avoin uusille kokemuksille (pidän uusien asioiden tekemisestä)

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

103 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
big5openness_01_T1	Kys0153.1: … avoin uusille kokemuksille (pidän uusien asioiden tekemisestä)	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	103	1062	1165	7	7: 309, 6: 241, 5: 203, 4: 179	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

big5openReverseCoded_02_T1

Kys0158.1: … tavallinen, en kovin luova

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

99 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
big5openReverseCoded_02_T1	Kys0158.1: … tavallinen, en kovin luova	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	99	1066	1165	7	4: 305, 5: 165, 6: 158, 7: 152	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

fatpct_T1

Rasva %

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

203 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist	format.spss	display_width
fatpct_T1	Rasva %	numeric	203	962	1165	25.27	8.98	5.7	18.2	24.45	31.28	60.5	<U+	2586><	U+2586> F5.2 0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_actplan_01_T1

Kys0115.1: … milloin liikkua

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

92 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_actplan_01_T1	Kys0115.1: … milloin liikkua	labelled	FALSE	Ei pidä paikkaansa1=1,Ei pidä enimmäkseen paikkaansa2=2,Pitää enimmäkseen paikkansa3=3,Pitää täysin paikkansa4=4	92	1073	1165	4	3: 400, 2: 246, 4: 223, 1: 204	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä paikkaansa1: 1
Ei pidä enimmäkseen paikkaansa2: 2
Pitää enimmäkseen paikkansa3: 3
Pitää täysin paikkansa4: 4

PA_actplan_02_T1

Kys0116.1: … missä liikkua

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

92 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_actplan_02_T1	Kys0116.1: … missä liikkua	labelled	FALSE	Ei pidä paikkaansa1=1,Ei pidä enimmäkseen paikkaansa2=2,Pitää enimmäkseen paikkansa3=3,Pitää täysin paikkansa4=4	92	1073	1165	4	3: 409, 4: 314, 2: 177, 1: 173	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä paikkaansa1: 1
Ei pidä enimmäkseen paikkaansa2: 2
Pitää enimmäkseen paikkansa3: 3
Pitää täysin paikkansa4: 4

PA_actplan_03_T1

Kys0117.1: … kuinka liikkua

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

92 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_actplan_03_T1	Kys0117.1: … kuinka liikkua	labelled	FALSE	Ei pidä paikkaansa1=1,Ei pidä enimmäkseen paikkaansa2=2,Pitää enimmäkseen paikkansa3=3,Pitää täysin paikkansa4=4	92	1073	1165	4	3: 459, 4: 305, 2: 155, 1: 154	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä paikkaansa1: 1
Ei pidä enimmäkseen paikkaansa2: 2
Pitää enimmäkseen paikkansa3: 3
Pitää täysin paikkansa4: 4

PA_actplan_04_T1

Kys0118.1: … kuinka usein liikkua

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

92 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_actplan_04_T1	Kys0118.1: … kuinka usein liikkua	labelled	FALSE	Ei pidä paikkaansa1=1,Ei pidä enimmäkseen paikkaansa2=2,Pitää enimmäkseen paikkansa3=3,Pitää täysin paikkansa4=4	92	1073	1165	4	3: 446, 4: 274, 2: 194, 1: 159	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä paikkaansa1: 1
Ei pidä enimmäkseen paikkaansa2: 2
Pitää enimmäkseen paikkansa3: 3
Pitää täysin paikkansa4: 4

PA_agrbct_01_T1

Kys0128.1: Olen asettanut itselleni liikuntatavoitteita.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

94 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_agrbct_01_T1	Kys0128.1: Olen asettanut itselleni liikuntatavoitteita.	labelled	FALSE	Ei pidä lainkaan paikkaansa0=1,1=2,2=3,3=4,4=5,Pitää täysin paikkansa5=6	94	1071	1165	6	6: 288, 1: 242, 4: 159, 5: 142	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa0: 1
1: 2
2: 3
3: 4
4: 5
Pitää täysin paikkansa5: 6

PA_agrbct_02_T1

Kys0129.1: Olen itse tehnyt tarkan suunnitelman (mitä, missä, milloin) omaehtoisen liikun

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

94 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_agrbct_02_T1	Kys0129.1: Olen itse tehnyt tarkan suunnitelman (mitä, missä, milloin) omaehtoisen liikun	labelled	FALSE	Ei pidä lainkaan paikkaansa0=1,1=2,2=3,3=4,4=5,Pitää täysin paikkansa5=6	94	1071	1165	6	1: 317, 6: 176, 4: 153, 3: 150	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa0: 1
1: 2
2: 3
3: 4
4: 5
Pitää täysin paikkansa5: 6

PA_agrbct_03_T1

Kys0130.1: Minulla on liikuntasuunnitelma, jonka joku muu, esim. liikuntaseurani, on tehnyt

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

94 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_agrbct_03_T1	Kys0130.1: Minulla on liikuntasuunnitelma, jonka joku muu, esim. liikuntaseurani, on tehnyt	labelled	FALSE	Ei pidä lainkaan paikkaansa0=1,1=2,2=3,3=4,4=5,Pitää täysin paikkansa5=6	94	1071	1165	6	1: 572, 6: 137, 3: 119, 4: 100	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa0: 1
1: 2
2: 3
3: 4
4: 5
Pitää täysin paikkansa5: 6

PA_agrbct_04_T1

Kys0131.1: Minulla on tapa, jolla muistutan itseäni liikuntasuunnitelmastani, esim. kirjoit

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

94 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_agrbct_04_T1	Kys0131.1: Minulla on tapa, jolla muistutan itseäni liikuntasuunnitelmastani, esim. kirjoit	labelled	FALSE	Ei pidä lainkaan paikkaansa0=1,1=2,2=3,3=4,4=5,Pitää täysin paikkansa5=6	94	1071	1165	6	1: 498, 2: 132, 3: 129, 4: 122	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa0: 1
1: 2
2: 3
3: 4
4: 5
Pitää täysin paikkansa5: 6

PA_agrbct_05_T1

Kys0132.1: Olen pilkkonut laajempia liikuntatavoitteitani pienempiin osatavoitteisiin.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

94 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_agrbct_05_T1	Kys0132.1: Olen pilkkonut laajempia liikuntatavoitteitani pienempiin osatavoitteisiin.	labelled	FALSE	Ei pidä lainkaan paikkaansa0=1,1=2,2=3,3=4,4=5,Pitää täysin paikkansa5=6	94	1071	1165	6	1: 421, 3: 192, 4: 151, 2: 138	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa0: 1
1: 2
2: 3
3: 4
4: 5
Pitää täysin paikkansa5: 6

PA_agrbct_06_T1

Kys0133.1: Olen kokeillut minulle uusia tapoja liikkua.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

94 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_agrbct_06_T1	Kys0133.1: Olen kokeillut minulle uusia tapoja liikkua.	labelled	FALSE	Ei pidä lainkaan paikkaansa0=1,1=2,2=3,3=4,4=5,Pitää täysin paikkansa5=6	94	1071	1165	6	1: 296, 4: 188, 3: 168, 6: 155	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa0: 1
1: 2
2: 3
3: 4
4: 5
Pitää täysin paikkansa5: 6

PA_agrbct_07_T1

Kys0134.1: Olen pohtinut, millaiset vaikeat tilanteet tai esteet estävät minua toteuttamast

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

94 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_agrbct_07_T1	Kys0134.1: Olen pohtinut, millaiset vaikeat tilanteet tai esteet estävät minua toteuttamast	labelled	FALSE	Ei pidä lainkaan paikkaansa0=1,1=2,2=3,3=4,4=5,Pitää täysin paikkansa5=6	94	1071	1165	6	1: 299, 3: 214, 4: 175, 2: 140	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa0: 1
1: 2
2: 3
3: 4
4: 5
Pitää täysin paikkansa5: 6

PA_agrbct_08_T1

Kys0135.1: Olen suunnitellut tapoja ylittää liikunnan harrastamisen esteitä.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

94 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_agrbct_08_T1	Kys0135.1: Olen suunnitellut tapoja ylittää liikunnan harrastamisen esteitä.	labelled	FALSE	Ei pidä lainkaan paikkaansa0=1,1=2,2=3,3=4,4=5,Pitää täysin paikkansa5=6	94	1071	1165	6	1: 285, 3: 204, 4: 178, 5: 148	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa0: 1
1: 2
2: 3
3: 4
4: 5
Pitää täysin paikkansa5: 6

PA_agrbct_09_T1

Kys0136.1: Olen miettinyt, miten liikunta sopii omaan minäkuvaani.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

94 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_agrbct_09_T1	Kys0136.1: Olen miettinyt, miten liikunta sopii omaan minäkuvaani.	labelled	FALSE	Ei pidä lainkaan paikkaansa0=1,1=2,2=3,3=4,4=5,Pitää täysin paikkansa5=6	94	1071	1165	6	5: 211, 1: 200, 4: 198, 6: 195	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa0: 1
1: 2
2: 3
3: 4
4: 5
Pitää täysin paikkansa5: 6

PA_agrbct_10_T1

Kys0137.1: Olen pyrkinyt löytämään tapoja liikkua siten, että se ei häiritse vaan tukee mui

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

94 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_agrbct_10_T1	Kys0137.1: Olen pyrkinyt löytämään tapoja liikkua siten, että se ei häiritse vaan tukee mui	labelled	FALSE	Ei pidä lainkaan paikkaansa0=1,1=2,2=3,3=4,4=5,Pitää täysin paikkansa5=6	94	1071	1165	6	1: 212, 6: 211, 4: 192, 5: 180	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa0: 1
1: 2
2: 3
3: 4
4: 5
Pitää täysin paikkansa5: 6

PA_amotivation_01_T1

Kys0082.1: En ymmärrä, miksi minun pitäisi liikkua vapaa-ajallani.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

103 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_amotivation_01_T1	Kys0082.1: En ymmärrä, miksi minun pitäisi liikkua vapaa-ajallani.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	103	1062	1165	5	1: 767, 2: 127, 3: 111, NA: 103	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_amotivation_02_T1

Kys0086.1: En näe mitään syytä liikkua vapaa-ajallani.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

108 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_amotivation_02_T1	Kys0086.1: En näe mitään syytä liikkua vapaa-ajallani.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	108	1057	1165	5	1: 756, 2: 131, 3: 108, NA: 108	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_amotivation_03_T1

Kys0096.1: En näe, mitä järkeä on liikkua vapaa-ajalla.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

98 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_amotivation_03_T1	Kys0096.1: En näe, mitä järkeä on liikkua vapaa-ajalla.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	98	1067	1165	5	1: 731, 2: 145, 3: 107, NA: 98	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_amotivation_04_T1

Kys0097.1: Mielestäni liikkuminen on ajanhukkaa.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

99 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_amotivation_04_T1	Kys0097.1: Mielestäni liikkuminen on ajanhukkaa.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	99	1066	1165	5	1: 802, 2: 111, NA: 99, 3: 93	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_copplan_01_T1

Kys0119.1: … mitä tehdä silloin, kun jokin sotkee suunnitelmani

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

92 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_copplan_01_T1	Kys0119.1: … mitä tehdä silloin, kun jokin sotkee suunnitelmani	labelled	FALSE	Ei pidä paikkaansa1=1,Ei pidä enimmäkseen paikkaansa2=2,Pitää enimmäkseen paikkansa3=3,Pitää täysin paikkansa4=4	92	1073	1165	4	3: 375, 2: 316, 1: 234, 4: 148	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä paikkaansa1: 1
Ei pidä enimmäkseen paikkaansa2: 2
Pitää enimmäkseen paikkansa3: 3
Pitää täysin paikkansa4: 4

PA_copplan_02_T1

Kys0120.1: … kuinka selviytyä repsahduksista

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

92 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_copplan_02_T1	Kys0120.1: … kuinka selviytyä repsahduksista	labelled	FALSE	Ei pidä paikkaansa1=1,Ei pidä enimmäkseen paikkaansa2=2,Pitää enimmäkseen paikkansa3=3,Pitää täysin paikkansa4=4	92	1073	1165	4	3: 367, 2: 314, 1: 230, 4: 162	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä paikkaansa1: 1
Ei pidä enimmäkseen paikkaansa2: 2
Pitää enimmäkseen paikkansa3: 3
Pitää täysin paikkansa4: 4

PA_copplan_03_T1

Kys0121.1: … kuinka pysyä suunnitelmissa vaikeissakin tilanteissa

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

92 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_copplan_03_T1	Kys0121.1: … kuinka pysyä suunnitelmissa vaikeissakin tilanteissa	labelled	FALSE	Ei pidä paikkaansa1=1,Ei pidä enimmäkseen paikkaansa2=2,Pitää enimmäkseen paikkansa3=3,Pitää täysin paikkansa4=4	92	1073	1165	4	3: 411, 2: 289, 1: 220, 4: 153	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä paikkaansa1: 1
Ei pidä enimmäkseen paikkaansa2: 2
Pitää enimmäkseen paikkansa3: 3
Pitää täysin paikkansa4: 4

PA_copplan_04_T1

Kys0122.1: … kuinka hyödyntää hyviä tilaisuuksia liikkumiseen

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

92 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_copplan_04_T1	Kys0122.1: … kuinka hyödyntää hyviä tilaisuuksia liikkumiseen	labelled	FALSE	Ei pidä paikkaansa1=1,Ei pidä enimmäkseen paikkaansa2=2,Pitää enimmäkseen paikkansa3=3,Pitää täysin paikkansa4=4	92	1073	1165	4	3: 447, 4: 233, 2: 224, 1: 169	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä paikkaansa1: 1
Ei pidä enimmäkseen paikkaansa2: 2
Pitää enimmäkseen paikkansa3: 3
Pitää täysin paikkansa4: 4

PA_dnorm_02_T1

Kys0107.1: Vanhempani liikkuvat säännöllisesti, vähintään 1,5 tuntia viikoittain

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

92 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_dnorm_02_T1	Kys0107.1: Vanhempani liikkuvat säännöllisesti, vähintään 1,5 tuntia viikoittain	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,3=3,4=4,5=5,6=6,Pitää täysin paikkansa7=7	92	1073	1165	7	7: 253, 4: 199, 2: 150, 5: 144	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_dnorm_01_T1

Kys0106.1: Suurin osa ystävistäni liikkuu säännöllisesti, vähintään 1,5 tuntia viikoittain

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

92 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_dnorm_01_T1	Kys0106.1: Suurin osa ystävistäni liikkuu säännöllisesti, vähintään 1,5 tuntia viikoittain	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,3=3,4=4,5=5,6=6,Pitää täysin paikkansa7=7	92	1073	1165	7	7: 238, 4: 218, 5: 168, 3: 160	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_controlled_01_T1

Kys0080.1: koska muut ihmiset sanovat, että minun pitää liikkua.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

97 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_controlled_01_T1	Kys0080.1: koska muut ihmiset sanovat, että minun pitää liikkua.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	97	1068	1165	5	1: 682, 2: 164, 3: 158, NA: 97	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_controlled_02_T1

Kys0081.1: koska muut ihmiset ovat tyytymättömiä minuun, jos en liiku.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

96 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_controlled_02_T1	Kys0081.1: koska muut ihmiset ovat tyytymättömiä minuun, jos en liiku.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	96	1069	1165	5	1: 784, 2: 129, 3: 109, NA: 96	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_controlled_03_T1

Kys0083.1: koska kaverini ja perheeni painostavat minua liikkumaan.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

101 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_controlled_03_T1	Kys0083.1: koska kaverini ja perheeni painostavat minua liikkumaan.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	101	1064	1165	5	1: 740, 2: 145, 3: 122, NA: 101	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_frqbct_01_T1

Kys0138.1: Olen muistuttanut mieleeni myös vapaa-ajallani, millaisia myönteisiä seurauksia

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

95 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_frqbct_01_T1	Kys0138.1: Olen muistuttanut mieleeni myös vapaa-ajallani, millaisia myönteisiä seurauksia	labelled	FALSE	En kertaakaan0=1,Kerran1=2,Kahdesti2=3,Viikoittain3=4,Noin joka toinen päivä4=5,Päivittäin5=6	95	1070	1165	6	4: 285, 6: 189, 3: 185, 5: 162	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

En kertaakaan0: 1
Kerran1: 2
Kahdesti2: 3
Viikoittain3: 4
Noin joka toinen päivä4: 5
Päivittäin5: 6

PA_frqbct_02_T1

Kys0139.1: Olen seurannut liikkumistani merkitsemällä liikuntakerrat paperiseen liikkumispä

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

95 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_frqbct_02_T1	Kys0139.1: Olen seurannut liikkumistani merkitsemällä liikuntakerrat paperiseen liikkumispä	labelled	FALSE	En kertaakaan0=1,Kerran1=2,Kahdesti2=3,Viikoittain3=4,Noin joka toinen päivä4=5,Päivittäin5=6	95	1070	1165	6	1: 718, 3: 102, NA: 95, 2: 83	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

En kertaakaan0: 1
Kerran1: 2
Kahdesti2: 3
Viikoittain3: 4
Noin joka toinen päivä4: 5
Päivittäin5: 6

PA_frqbct_03_T1

Kys0140.1: Olen seurannut liikkumistani käyttämällä älypuhelinta, esim. Moves-appia.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

95 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_frqbct_03_T1	Kys0140.1: Olen seurannut liikkumistani käyttämällä älypuhelinta, esim. Moves-appia.	labelled	FALSE	En kertaakaan0=1,Kerran1=2,Kahdesti2=3,Viikoittain3=4,Noin joka toinen päivä4=5,Päivittäin5=6	95	1070	1165	6	1: 669, 3: 118, NA: 95, 4: 86	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

En kertaakaan0: 1
Kerran1: 2
Kahdesti2: 3
Viikoittain3: 4
Noin joka toinen päivä4: 5
Päivittäin5: 6

PA_frqbct_04_T1

Kys0141.1: Käytän muistivihjeitä, joiden avulla muistan toteuttaa liikunta-aikomukseni.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

95 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_frqbct_04_T1	Kys0141.1: Käytän muistivihjeitä, joiden avulla muistan toteuttaa liikunta-aikomukseni.	labelled	FALSE	En kertaakaan0=1,Kerran1=2,Kahdesti2=3,Viikoittain3=4,Noin joka toinen päivä4=5,Päivittäin5=6	95	1070	1165	6	1: 696, 3: 109, NA: 95, 2: 90	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

En kertaakaan0: 1
Kerran1: 2
Kahdesti2: 3
Viikoittain3: 4
Noin joka toinen päivä4: 5
Päivittäin5: 6

PA_frqbct_05_T1

Kys0142.1: Olen verrannut toteutunutta liikuntaani asettamaani liikuntatavoitteeseen.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

95 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_frqbct_05_T1	Kys0142.1: Olen verrannut toteutunutta liikuntaani asettamaani liikuntatavoitteeseen.	labelled	FALSE	En kertaakaan0=1,Kerran1=2,Kahdesti2=3,Viikoittain3=4,Noin joka toinen päivä4=5,Päivittäin5=6	95	1070	1165	6	1: 494, 4: 152, 3: 147, 2: 117	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

En kertaakaan0: 1
Kerran1: 2
Kahdesti2: 3
Viikoittain3: 4
Noin joka toinen päivä4: 5
Päivittäin5: 6

PA_frqbct_06_T1

Kys0143.1: Olen miettinyt, mitkä liikunnan harrastamisen syyt ovat minulle itselleni tärkei

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

95 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_frqbct_06_T1	Kys0143.1: Olen miettinyt, mitkä liikunnan harrastamisen syyt ovat minulle itselleni tärkei	labelled	FALSE	En kertaakaan0=1,Kerran1=2,Kahdesti2=3,Viikoittain3=4,Noin joka toinen päivä4=5,Päivittäin5=6	95	1070	1165	6	1: 233, 4: 215, 3: 193, 6: 181	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

En kertaakaan0: 1
Kerran1: 2
Kahdesti2: 3
Viikoittain3: 4
Noin joka toinen päivä4: 5
Päivittäin5: 6

PA_frqbct_07_T1

Kys0144.1: Olen tehnyt muutoksia kotiini (esim. huoneeseeni tai tietokoneelleni), jotta lii

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

95 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_frqbct_07_T1	Kys0144.1: Olen tehnyt muutoksia kotiini (esim. huoneeseeni tai tietokoneelleni), jotta lii	labelled	FALSE	En kertaakaan0=1,Kerran1=2,Kahdesti2=3,Viikoittain3=4,Noin joka toinen päivä4=5,Päivittäin5=6	95	1070	1165	6	1: 591, 2: 123, 4: 114, 3: 111	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

En kertaakaan0: 1
Kerran1: 2
Kahdesti2: 3
Viikoittain3: 4
Noin joka toinen päivä4: 5
Päivittäin5: 6

PA_frqbct_08_T1

Kys0145.1: Olen pyytänyt kavereiltani tai perheeltäni tukea liikuntatavoitteideni saavuttam

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

95 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_frqbct_08_T1	Kys0145.1: Olen pyytänyt kavereiltani tai perheeltäni tukea liikuntatavoitteideni saavuttam	labelled	FALSE	En kertaakaan0=1,Kerran1=2,Kahdesti2=3,Viikoittain3=4,Noin joka toinen päivä4=5,Päivittäin5=6	95	1070	1165	6	1: 512, 3: 142, 2: 139, 4: 123	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

En kertaakaan0: 1
Kerran1: 2
Kahdesti2: 3
Viikoittain3: 4
Noin joka toinen päivä4: 5
Päivittäin5: 6

PA_frqbct_09_T1

Kys0146.1: Jos en ole saavuttanut liikuntatavoitettani, olen arvioinut, mikä meni pieleen.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

95 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_frqbct_09_T1	Kys0146.1: Jos en ole saavuttanut liikuntatavoitettani, olen arvioinut, mikä meni pieleen.	labelled	FALSE	En kertaakaan0=1,Kerran1=2,Kahdesti2=3,Viikoittain3=4,Noin joka toinen päivä4=5,Päivittäin5=6,Saavutin tavoitteeni6=7	95	1070	1165	7	1: 393, 4: 177, 2: 163, 3: 149	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

En kertaakaan0: 1
Kerran1: 2
Kahdesti2: 3
Viikoittain3: 4
Noin joka toinen päivä4: 5
Päivittäin5: 6
Saavutin tavoitteeni6: 7

PA_goal_01_T1

Kys0147.1: Onko sinulla tällä hetkellä liikuntatavoite?

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

104 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_goal_01_T1	Kys0147.1: Onko sinulla tällä hetkellä liikuntatavoite?	labelled	FALSE	Kyllä (kerro lyhyesti, mikä tämänhetkinen liikuntatavoittees=0,Ei=1	104	1061	1165	2	1: 592, 0: 469, NA: 104	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Kyllä (kerro lyhyesti, mikä tämänhetkinen liikuntatavoittees: 0
Ei: 1

PA_autonomous_01_T1

Kys0087.1: koska minusta on tärkeää nähdä vaivaa säännöllisen liikunnan eteen.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

102 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_autonomous_01_T1	Kys0087.1: koska minusta on tärkeää nähdä vaivaa säännöllisen liikunnan eteen.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	102	1063	1165	5	3: 298, 4: 240, 5: 196, 1: 178	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_autonomous_02_T1

Kys0088.1: koska arvostan liikunnasta saamaani hyötyä.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

102 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_autonomous_02_T1	Kys0088.1: koska arvostan liikunnasta saamaani hyötyä.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	102	1063	1165	5	5: 391, 4: 275, 3: 225, NA: 102	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_autonomous_03_T1

Kys0090.1: koska minulle on tärkeää liikkua säännöllisesti.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

95 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_autonomous_03_T1	Kys0090.1: koska minulle on tärkeää liikkua säännöllisesti.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	95	1070	1165	5	3: 283, 5: 280, 4: 224, 2: 175	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_inorm_01_T1

Kys0108.1: Vanhempani haluaisivat minun liikkuvan säännöllisesti, vähintään 1,5 tuntia viik

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

92 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_inorm_01_T1	Kys0108.1: Vanhempani haluaisivat minun liikkuvan säännöllisesti, vähintään 1,5 tuntia viik	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,3=3,4=4,5=5,6=6,Pitää täysin paikkansa7=7	92	1073	1165	7	7: 306, 4: 219, 6: 136, 3: 117	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_autonomous_04_T1

Kys0089.1: koska se sopii yhteen elämäntavoitteideni kanssa.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

95 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_autonomous_04_T1	Kys0089.1: koska se sopii yhteen elämäntavoitteideni kanssa.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	95	1070	1165	5	3: 338, 5: 260, 4: 196, 2: 152	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_autonomous_05_T1

Kys0092.1: …koska liikunta sopii yhteen arvojeni kanssa.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

103 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_autonomous_05_T1	Kys0092.1: …koska liikunta sopii yhteen arvojeni kanssa.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	103	1062	1165	5	3: 311, 5: 239, 4: 221, 2: 161	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_autonomous_06_T1

Kys0094.1: koska liikunta on keskeinen osa sitä, kuka olen.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

99 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_autonomous_06_T1	Kys0094.1: koska liikunta on keskeinen osa sitä, kuka olen.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	99	1066	1165	5	3: 256, 5: 224, 4: 206, 2: 201	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_intention_01_T1

Kys0113.1: Aion liikkua säännöllisesti viikoittain vähintään 1,5 tuntia seuraavan kuukauden

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

92 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_intention_01_T1	Kys0113.1: Aion liikkua säännöllisesti viikoittain vähintään 1,5 tuntia seuraavan kuukauden	labelled	FALSE	Epätodennäköistä1=1,2=2,3=3,4=4,5=5,6=6,Todennäköistä7=7	92	1073	1165	7	7: 511, 4: 130, 6: 111, 5: 108	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Epätodennäköistä1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Todennäköistä7: 7

PA_intention_02_T1

Kys0114.1: Aion liikkua säännöllisesti viikoittain vähintään 1,5 tuntia seuraavan kuukauden

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

92 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_intention_02_T1	Kys0114.1: Aion liikkua säännöllisesti viikoittain vähintään 1,5 tuntia seuraavan kuukauden	labelled	FALSE	Ehdottomasti en1=1,2=2,3=3,4=4,5=5,6=6,Ehdottomasti kyllä7=7	92	1073	1165	7	7: 498, 4: 165, 6: 115, 5: 111	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ehdottomasti en1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Ehdottomasti kyllä7: 7

PA_autonomous_07_T1

Kys0091.1: koska tunnen iloa ja tyytyväisyyttä, kun liikun.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

95 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_autonomous_07_T1	Kys0091.1: koska tunnen iloa ja tyytyväisyyttä, kun liikun.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	95	1070	1165	5	5: 372, 4: 278, 3: 240, 2: 109	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_autonomous_08_T1

Kys0093.1: koska liikkuminen on hauskaa.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

99 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_autonomous_08_T1	Kys0093.1: koska liikkuminen on hauskaa.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	99	1066	1165	5	5: 323, 4: 294, 3: 258, 2: 115	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_autonomous_09_T1

Kys0095.1: koska nautin liikuntahetkistä.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

108 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_autonomous_09_T1	Kys0095.1: koska nautin liikuntahetkistä.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	108	1057	1165	5	5: 295, 3: 264, 4: 264, 2: 138	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_controlled_04_T1

Kys0084.1: koska tunnen syyllisyyttä, jos en liiku.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

97 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_controlled_04_T1	Kys0084.1: koska tunnen syyllisyyttä, jos en liiku.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	97	1068	1165	5	1: 518, 3: 219, 2: 134, 4: 108	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_controlled_05_T1

Kys0085.1: koska tunnen itseni epäonnistuneeksi, jos en ole liikkunut vähään aikaan.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

99 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_controlled_05_T1	Kys0085.1: koska tunnen itseni epäonnistuneeksi, jos en ole liikkunut vähään aikaan.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	99	1066	1165	5	1: 457, 3: 212, 2: 161, 4: 135	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_outcomeExpectations_01_T1

Kys0068.1: Se saisi minut hyvälle tuulelle

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

94 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_outcomeExpectations_01_T1	Kys0068.1: Se saisi minut hyvälle tuulelle	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	94	1071	1165	7	7: 377, 6: 211, 5: 207, 4: 153	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_outcomeExpectations_03_T1

Kys0070.1: Se auttaisi pitämään painoni kurissa

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

101 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_outcomeExpectations_03_T1	Kys0070.1: Se auttaisi pitämään painoni kurissa	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	101	1064	1165	7	7: 367, 4: 226, 6: 162, 5: 156	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_outcomeExpectations_04_T1

Kys0071.1: Se auttaisi kasvattamaan lihasmassaa

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

94 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_outcomeExpectations_04_T1	Kys0071.1: Se auttaisi kasvattamaan lihasmassaa	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	94	1071	1165	7	7: 365, 6: 227, 5: 208, 4: 157	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_outcomeExpectations_05_T1

Kys0072.1: Se parantaisi kykyäni tehdä töitä ja päivittäisiä askareitani

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

98 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_outcomeExpectations_05_T1	Kys0072.1: Se parantaisi kykyäni tehdä töitä ja päivittäisiä askareitani	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	98	1067	1165	7	7: 276, 5: 245, 4: 207, 6: 200	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_outcomeExpectations_06_T1

Kys0073.1: Se auttaisi minua jaksamaan

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

94 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_outcomeExpectations_06_T1	Kys0073.1: Se auttaisi minua jaksamaan	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	94	1071	1165	7	7: 323, 5: 233, 6: 231, 4: 175	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_outcomeExpectations_07_T1

Kys0074.1: Saisin sen avulla uusia kokemuksia

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

103 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_outcomeExpectations_07_T1	Kys0074.1: Saisin sen avulla uusia kokemuksia	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	103	1062	1165	7	4: 276, 7: 225, 5: 219, 6: 176	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_outcomeExpectations_10_T1

Kys0077.1: Se auttaisi minua nukkumaan paremmin

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

96 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_outcomeExpectations_10_T1	Kys0077.1: Se auttaisi minua nukkumaan paremmin	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	96	1069	1165	7	7: 350, 6: 236, 4: 179, 5: 164	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_outcomeExpectations_11_T1

Kys0078.1: Saisin sen avulla onnistumisen kokemuksia

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

102 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_outcomeExpectations_11_T1	Kys0078.1: Saisin sen avulla onnistumisen kokemuksia	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	102	1063	1165	7	7: 293, 4: 228, 6: 206, 5: 179	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_outcomeExpectations_12_T1

Kys0079.1: Se tukisi itsetuntoani

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

95 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_outcomeExpectations_12_T1	Kys0079.1: Se tukisi itsetuntoani	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	95	1070	1165	7	7: 333, 4: 234, 6: 191, 5: 158	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_outcomeExpectationsNegative_02_T1

Kys0069.1: Se veisi liikaa aikaa muilta elämäni tärkeiltä asioilta

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

99 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_outcomeExpectationsNegative_02_T1	Kys0069.1: Se veisi liikaa aikaa muilta elämäni tärkeiltä asioilta	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	99	1066	1165	7	1: 296, 4: 225, 2: 223, 3: 149	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_outcomeExpectationsNegative_08_T1

Kys0075.1: Se olisi stressaavaa ja henkisesti rasittavaa

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

102 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_outcomeExpectationsNegative_08_T1	Kys0075.1: Se olisi stressaavaa ja henkisesti rasittavaa	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	102	1063	1165	7	1: 380, 2: 259, 4: 176, 3: 119	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_outcomeExpectationsNegative_09_T1

Kys0076.1: Se olisi ikävällä tavalla fyysisesti väsyttävää

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

101 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_outcomeExpectationsNegative_09_T1	Kys0076.1: Se olisi ikävällä tavalla fyysisesti väsyttävää	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	101	1064	1165	7	1: 372, 2: 249, 4: 199, 3: 116	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_opportunities_01_T1

Kys0098.1: Minulla on riittävästi rahaa liikunnan harrastamiseen

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

95 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_opportunities_01_T1	Kys0098.1: Minulla on riittävästi rahaa liikunnan harrastamiseen	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Pitää täysin paikkansa7=7	95	1070	1165	7	7: 307, 4: 203, 5: 146, 6: 122	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_opportunities_02_T1

Kys0099.1: Ympäristössäni on hyviä pyöräteitä ja lenkkipolkuja

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

98 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_opportunities_02_T1	Kys0099.1: Ympäristössäni on hyviä pyöräteitä ja lenkkipolkuja	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Pitää täysin paikkansa7=7	98	1067	1165	7	7: 400, 6: 236, 5: 164, 4: 140	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_opportunities_04_T1

Kys0101.1: Lähistölläni on paljon hyviä liikuntapaikkoja (esim. urheiluhalleja, kuntosaleja

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

95 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_opportunities_04_T1	Kys0101.1: Lähistölläni on paljon hyviä liikuntapaikkoja (esim. urheiluhalleja, kuntosaleja	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Pitää täysin paikkansa7=7	95	1070	1165	7	7: 437, 6: 207, 5: 151, 4: 148	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_opportunities_05_T1

Kys0102.1: Liikuntavälineiden puute ei ole este liikkumiselleni

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

101 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_opportunities_05_T1	Kys0102.1: Liikuntavälineiden puute ei ole este liikkumiselleni	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Pitää täysin paikkansa7=7	101	1064	1165	7	7: 434, 4: 177, 6: 161, 5: 120	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_opportunities_07_T1

Kys0104.1: Minulla on paljon mahdollisuuksia harrastaa liikuntaa kotona

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

97 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_opportunities_07_T1	Kys0104.1: Minulla on paljon mahdollisuuksia harrastaa liikuntaa kotona	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Pitää täysin paikkansa7=7	97	1068	1165	7	4: 228, 7: 219, 5: 185, 6: 160	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_opportunitiesReverseCoded_03_T1

Kys0100.1: Minulla ei ole tarvitsemiani liikuntavälineitä

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

100 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_opportunitiesReverseCoded_03_T1	Kys0100.1: Minulla ei ole tarvitsemiani liikuntavälineitä	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Pitää täysin paikkansa7=7	100	1065	1165	7	7: 375, 4: 206, 6: 184, NA: 100	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_opportunitiesReverseCoded_06_T1

Kys0103.1: Minulla on paljon kiireitä koulun, harrastusten ja/tai kaverien vuoksi

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

106 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_opportunitiesReverseCoded_06_T1	Kys0103.1: Minulla on paljon kiireitä koulun, harrastusten ja/tai kaverien vuoksi	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Pitää täysin paikkansa7=7	106	1059	1165	7	4: 248, 1: 180, 2: 161, 3: 148	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_opportunitiesReverseCoded_08_T1

Kys0105.1: Uskontoni tai perheeni uskonto rajoittaa liikkumistani

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

99 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_opportunitiesReverseCoded_08_T1	Kys0105.1: Uskontoni tai perheeni uskonto rajoittaa liikkumistani	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Pitää täysin paikkansa7=7	99	1066	1165	7	7: 918, NA: 99, 4: 65, 6: 28	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_pbc_01_T1

Kys0125.1: Voin itse täysin vaikuttaa siihen, liikunko säännöllisesti.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

96 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_pbc_01_T1	Kys0125.1: Voin itse täysin vaikuttaa siihen, liikunko säännöllisesti.	labelled	FALSE	Ei pidä lainkaan paikkaansa1=1,2=2,3=3,4=4,5=5,6=6,Pitää täysin paikkansa7=7	96	1069	1165	7	7: 532, 6: 192, 5: 152, 4: 101	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_pbc_03_T1

Kys0127.1: Olen varma, että pystyisin voittamaan hankaluudet, jotka estävät minua liikkumas

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

99 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_pbc_03_T1	Kys0127.1: Olen varma, että pystyisin voittamaan hankaluudet, jotka estävät minua liikkumas	labelled	FALSE	Ei pidä lainkaan paikkaansa1=1,2=2,3=3,4=4,5=5,6=6,Pitää täysin paikkansa7=7	99	1066	1165	7	7: 346, 4: 191, 6: 179, 5: 173	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_pbcReverseCoded_02_T1

Kys0126.1: Liikkuminen säännöllisesti ei riipu täysin minusta.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

102 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_pbcReverseCoded_02_T1	Kys0126.1: Liikkuminen säännöllisesti ei riipu täysin minusta.	labelled	FALSE	Ei pidä lainkaan paikkaansa1=1,2=2,3=3,4=4,5=5,6=6,Pitää täysin paikkansa7=7	102	1063	1165	7	7: 355, 6: 170, 4: 157, 5: 109	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_selfefficacy_01_T1

Kys0123.1: Jos haluaisin, voisin liikkua säännöllisesti.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

94 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_selfefficacy_01_T1	Kys0123.1: Jos haluaisin, voisin liikkua säännöllisesti.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,4=4,5=5,6=6,Täysin samaa mieltä7=7	94	1071	1165	7	7: 570, 5: 151, 6: 137, 4: 121	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_selfefficacyReverseCoded_02_T1

Kys0124.1: Liikkuminen säännöllisesti on minulle

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

94 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_selfefficacyReverseCoded_02_T1	Kys0124.1: Liikkuminen säännöllisesti on minulle	labelled	FALSE	Helppoa1=1,2=2,3=3,4=4,5=5,6=6,Vaikeaa7=7	94	1071	1165	7	7: 260, 4: 202, 5: 158, 3: 138	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Helppoa1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Vaikeaa7: 7

paAccelerometer_T1

Keskimääräinen reippaan ja rasittavan liikunnan (MVPA) minuutit päivässä (T1)

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

452 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist	format.spss	display_width
paAccelerometer_T1	Keskimääräinen reippaan ja rasittavan liikunnan (MVPA) minuutit päivässä (T1)	numeric	452	713	1165	183.76	53.84	61.52	145.34	180.93	217.74	367.21	<U+	2585><	U+2587> F8.2 0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

padaysLastweek_T1

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

83 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
padaysLastweek_T1	labelled	FALSE	0 (en yhtenäkään)=0,1=1,2=2,3=3,4=4,5=5,6=6,7=7	83	1082	1165	8	3: 233, 2: 202, 0: 158, 4: 151	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

0 (en yhtenäkään): 0
1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
7: 7

pafreqUsually_T1

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

83 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
pafreqUsually_T1	labelled	FALSE	En voi vamman tai sairauden takia harrastaa liikuntaa=0,Harvemmin kuin kerran viikossa=1,1-2 kertaa viikossa=2,3 kertaa viikossa=3,4 kertaa viikossa=4,5 kertaa viikossa tai useammin=5	83	1082	1165	6	2: 326, 1: 258, 3: 197, 4: 145	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

En voi vamman tai sairauden takia harrastaa liikuntaa: 0
Harvemmin kuin kerran viikossa: 1
1-2 kertaa viikossa: 2
3 kertaa viikossa: 3
4 kertaa viikossa: 4
5 kertaa viikossa tai useammin: 5

pahrsLastweek_T1

Kys0046.1: Yhteensä - Tuntia:

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

83 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
pahrsLastweek_T1	Kys0046.1: Yhteensä - Tuntia:	labelled	FALSE	0=1,1=2,2=3,3=4,4=5,5=6,6=7,7=8,8=9,9=10,10=11,11=12,12=13,13=14,14=15,15=16,16=17,17=18,18=19,19=20,20=21,21=22,22=23,23=24,24=25,25=26,26=27,27=28,28=29,29=30,30=31,31=32,32=33,33=34,34=35,35=36,36=37,37=38,38=39,39=40,40=41,41=42,42=43,43=44,44=45,45=46,46=47,47=48,48=49,49=50,50=51,51=52,52=53,53=54,54=55,55=56,56=57,57=58,58=59,59=60,60=61	83	1082	1165	38	1: 188, 2: 175, 3: 145, 4: 121	F2.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

pahrsUsually_T1

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

83 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
pahrsUsually_T1	labelled	FALSE	En yhtään=0,Noin puoli tuntia=1,Noin 1 tunnin=2,Noin 1,5 tuntia=3,Noin 2-3 tuntia=4,Noin 4-6 tuntia=5,Noin 7 tuntia tai enemmän=6	83	1082	1165	7	4: 219, 5: 175, 1: 168, 2: 147	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

En yhtään: 0
Noin puoli tuntia: 1
Noin 1 tunnin: 2
Noin 1,5 tuntia: 3
Noin 2-3 tuntia: 4
Noin 4-6 tuntia: 5
Noin 7 tuntia tai enemmän: 6

paminLastweek_T1

Kys0047.1: Yhteensä - Minuuttia:

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

83 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
paminLastweek_T1	Kys0047.1: Yhteensä - Minuuttia:	labelled	FALSE	0=1,30=2	83	1082	1165	2	1: 596, 2: 486, NA: 83	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

0: 1
30: 2

SB_dnorm_01_T1

Kys0178.1: yrittää rajoittaa omaa istumistaan KOULUPÄIVÄN aikana.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

106 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_dnorm_01_T1	Kys0178.1: yrittää rajoittaa omaa istumistaan KOULUPÄIVÄN aikana.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	106	1059	1165	7	4: 472, 1: 283, 2: 117, NA: 106	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_dnorm_02_T1

Kys0179.1: yrittää rajoittaa omaa istumistaan VAPAA-AJALLA.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

105 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_dnorm_02_T1	Kys0179.1: yrittää rajoittaa omaa istumistaan VAPAA-AJALLA.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	105	1060	1165	7	4: 499, 1: 210, 2: 105, NA: 105	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_inorm_01_T1

Kys0180.1: pitää hyväksyttävänä, että yritän rajoittaa omaa istumistani KOULUSSA.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

109 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_inorm_01_T1	Kys0180.1: pitää hyväksyttävänä, että yritän rajoittaa omaa istumistani KOULUSSA.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	109	1056	1165	7	4: 568, 1: 127, NA: 109, 7: 92	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_inorm_02_T1

Kys0181.1: Suurin osa opettajistani hyväksyisi sen, jos rajoitan omaa istumistani KOULUSSA.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

112 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_inorm_02_T1	Kys0181.1: Suurin osa opettajistani hyväksyisi sen, jos rajoitan omaa istumistani KOULUSSA.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	112	1053	1165	7	4: 511, 5: 122, NA: 112, 7: 96	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_intention_01_T1

Kys0187.1: Aion rajoittaa omaa istumistani seuraavan kuukauden aikana KOULUSSA.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

106 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_intention_01_T1	Kys0187.1: Aion rajoittaa omaa istumistani seuraavan kuukauden aikana KOULUSSA.	labelled	FALSE	Epätodennäköistä1=1,2=2,3=3,4=4,5=5,6=6,Todennäköistä7=7	106	1059	1165	7	4: 276, 1: 257, 3: 144, 2: 132	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Epätodennäköistä1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Todennäköistä7: 7

SB_intention_02_T1

Kys0188.1: Aion rajoittaa omaa istumistani seuraavan kuukauden aikana KOULUSSA.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

109 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_intention_02_T1	Kys0188.1: Aion rajoittaa omaa istumistani seuraavan kuukauden aikana KOULUSSA.	labelled	FALSE	Ehdottomasti en1=1,2=2,3=3,4=4,5=5,6=6,Ehdottomasti kyllä7=7	109	1056	1165	7	4: 320, 1: 168, 3: 165, 2: 163	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ehdottomasti en1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Ehdottomasti kyllä7: 7

SB_intention_03_T1

Kys0189.1: Aion rajoittaa omaa istumistani seuraavan kuukauden aikana VAPAA-AJALLA.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

111 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_intention_03_T1	Kys0189.1: Aion rajoittaa omaa istumistani seuraavan kuukauden aikana VAPAA-AJALLA.	labelled	FALSE	Epätodennäköistä1=1,2=2,3=3,4=4,5=5,6=6,Todennäköistä7=7	111	1054	1165	7	4: 253, 1: 164, 5: 150, 7: 149	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Epätodennäköistä1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Todennäköistä7: 7

SB_intention_04_T1

Kys0190.1: Aion rajoittaa omaa istumistani seuraavan kuukauden aikana VAPAA-AJALLA.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

110 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_intention_04_T1	Kys0190.1: Aion rajoittaa omaa istumistani seuraavan kuukauden aikana VAPAA-AJALLA.	labelled	FALSE	Ehdottomasti en1=1,2=2,3=3,4=4,5=5,6=6,Ehdottomasti kyllä7=7	110	1055	1165	7	4: 271, 5: 156, 3: 140, 7: 140	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ehdottomasti en1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Ehdottomasti kyllä7: 7

SB_outcomeExpectationsNegative_01_T1

Kys0171.1: … oloni olisi epämukava.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

102 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_outcomeExpectationsNegative_01_T1	Kys0171.1: … oloni olisi epämukava.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	102	1063	1165	7	4: 394, 1: 222, 2: 131, 3: 117	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_outcomeExpectations_02_T1

Kys0172.1: … virkistyisin ja jaksaisin paremmin.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

109 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_outcomeExpectations_02_T1	Kys0172.1: … virkistyisin ja jaksaisin paremmin.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	109	1056	1165	7	4: 301, 5: 236, 7: 197, 6: 164	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_outcomeExpectations_03_T1

Kys0173.1: keskittymiskykyni paranisi.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

107 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_outcomeExpectations_03_T1	Kys0173.1: keskittymiskykyni paranisi.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	107	1058	1165	7	4: 326, 5: 209, 7: 183, 6: 145	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_outcomeExpectations_04_T1

Kys0174.1: niska-, hartia- ja selkäkivut sekä päänsäryt vähenisivät.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

102 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_outcomeExpectations_04_T1	Kys0174.1: niska-, hartia- ja selkäkivut sekä päänsäryt vähenisivät.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	102	1063	1165	7	4: 268, 7: 259, 6: 189, 5: 182	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_outcomeExpectations_05_T1

Kys0175.1: lihakseni eivät rappeutuisi.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

105 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_outcomeExpectations_05_T1	Kys0175.1: lihakseni eivät rappeutuisi.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	105	1060	1165	7	4: 278, 7: 238, 5: 199, 6: 186	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_outcomeExpectations_06_T1

Kys0176.1: aivoni toimisivat paremmin.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

107 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_outcomeExpectations_06_T1	Kys0176.1: aivoni toimisivat paremmin.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	107	1058	1165	7	4: 298, 7: 224, 5: 197, 6: 179	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_outcomeExpectationsNegative_07_T1

Kys0177.1: se häiritsisi asioiden tekemistä.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

108 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_outcomeExpectationsNegative_07_T1	Kys0177.1: se häiritsisi asioiden tekemistä.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	108	1057	1165	7	4: 331, 1: 225, 2: 158, 3: 122	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_sePbc_01_T1

Kys0182.1: Jos haluan, voin rajoittaa omaa istumistani KOULUSSA.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

103 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_sePbc_01_T1	Kys0182.1: Jos haluan, voin rajoittaa omaa istumistani KOULUSSA.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	103	1062	1165	7	4: 326, 5: 192, 7: 159, 6: 109	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_sePbc_02_T1

Kys0183.1: Voin itse täysin vaikuttaa siihen rajoitanko omaa istumistani KOULUSSA.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

104 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_sePbc_02_T1	Kys0183.1: Voin itse täysin vaikuttaa siihen rajoitanko omaa istumistani KOULUSSA.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	104	1061	1165	7	4: 353, 5: 172, 7: 156, NA: 104	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_sePbc_03_T1

Kys0184.1: Jos haluan, voin rajoittaa omaa istumistani VAPAA-AJALLA.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

105 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_sePbc_03_T1	Kys0184.1: Jos haluan, voin rajoittaa omaa istumistani VAPAA-AJALLA.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	105	1060	1165	7	7: 506, 4: 180, 6: 171, 5: 127	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_sePbc_04_T1

Kys0185.1: Voin itse täysin vaikuttaa siihen rajoitanko omaa istumistani VAPAA-AJALLA.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

105 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_sePbc_04_T1	Kys0185.1: Voin itse täysin vaikuttaa siihen rajoitanko omaa istumistani VAPAA-AJALLA.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	105	1060	1165	7	7: 504, 4: 192, 6: 171, 5: 121	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_sePbc_05_T1

Kys0186.1: Jos haluan, voin rajoittaa omaa istumistani TYÖSSÄ OPPIMASSA.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

111 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_sePbc_05_T1	Kys0186.1: Jos haluan, voin rajoittaa omaa istumistani TYÖSSÄ OPPIMASSA.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	111	1054	1165	7	4: 377, 7: 242, 5: 131, 6: 111	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

sitLieAccelerometer_T1

Keskimääräinen makuun ja istumisen (SB) aika päivässä (T1)

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

452 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist	format.spss	display_width
sitLieAccelerometer_T1	Keskimääräinen makuun ja istumisen (SB) aika päivässä (T1)	numeric	452	713	1165	578.21	97.15	304.76	514.36	567.97	634.22	936.09	<U+	2582><	U+2587> F8.2 0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

symptom_neckShoulderPain_T1

Kys0031.1: Niska- tai hartiakipuja

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

118 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
symptom_neckShoulderPain_T1	Kys0031.1: Niska- tai hartiakipuja	labelled	FALSE	Harvoin tai ei lainkaan=1,Noin kerran kuussa=2,Noin kerran viikossa=3,Lähes joka päivä=4	118	1047	1165	4	1: 457, 2: 300, 3: 182, NA: 118	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Harvoin tai ei lainkaan: 1
Noin kerran kuussa: 2
Noin kerran viikossa: 3
Lähes joka päivä: 4

symptom_lowerBackPain_T1

Kys0032.1: Selän alaosan kipuja

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

112 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
symptom_lowerBackPain_T1	Kys0032.1: Selän alaosan kipuja	labelled	FALSE	Harvoin tai ei lainkaan=1,Noin kerran kuussa=2,Noin kerran viikossa=3,Lähes joka päivä=4	112	1053	1165	4	1: 527, 2: 321, 3: 141, NA: 112	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Harvoin tai ei lainkaan: 1
Noin kerran kuussa: 2
Noin kerran viikossa: 3
Lähes joka päivä: 4

symptom_stomachAche_T1

Kys0033.1: Vatsakipuja

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

139 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
symptom_stomachAche_T1	Kys0033.1: Vatsakipuja	labelled	FALSE	Harvoin tai ei lainkaan=1,Noin kerran kuussa=2,Noin kerran viikossa=3,Lähes joka päivä=4	139	1026	1165	4	1: 454, 2: 434, NA: 139, 3: 106	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Harvoin tai ei lainkaan: 1
Noin kerran kuussa: 2
Noin kerran viikossa: 3
Lähes joka päivä: 4

symptom_tensionNervousness_T1

Kys0034.1: Jännittyneisyyttä tai hermostuneisuutta

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

114 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
symptom_tensionNervousness_T1	Kys0034.1: Jännittyneisyyttä tai hermostuneisuutta	labelled	FALSE	Harvoin tai ei lainkaan=1,Noin kerran kuussa=2,Noin kerran viikossa=3,Lähes joka päivä=4	114	1051	1165	4	1: 463, 2: 306, 3: 203, NA: 114	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Harvoin tai ei lainkaan: 1
Noin kerran kuussa: 2
Noin kerran viikossa: 3
Lähes joka päivä: 4

symptom_irritabilityAngerbursts_T1

Kys0035.1: Ärtyneisyyttä tai kiukunpurkauksia

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

126 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
symptom_irritabilityAngerbursts_T1	Kys0035.1: Ärtyneisyyttä tai kiukunpurkauksia	labelled	FALSE	Harvoin tai ei lainkaan=1,Noin kerran kuussa=2,Noin kerran viikossa=3,Lähes joka päivä=4	126	1039	1165	4	1: 462, 2: 287, 3: 224, NA: 126	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Harvoin tai ei lainkaan: 1
Noin kerran kuussa: 2
Noin kerran viikossa: 3
Lähes joka päivä: 4

symptom_sleepDifficulty_T1

Kys0036.1: Vaikeuksia päästä uneen tai heräilemistä öisin

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

113 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
symptom_sleepDifficulty_T1	Kys0036.1: Vaikeuksia päästä uneen tai heräilemistä öisin	labelled	FALSE	Harvoin tai ei lainkaan=1,Noin kerran kuussa=2,Noin kerran viikossa=3,Lähes joka päivä=4	113	1052	1165	4	1: 438, 2: 243, 3: 219, 4: 152	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Harvoin tai ei lainkaan: 1
Noin kerran kuussa: 2
Noin kerran viikossa: 3
Lähes joka päivä: 4

symptom_headAche_T1

Kys0037.1: Päänsärkyä

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

110 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
symptom_headAche_T1	Kys0037.1: Päänsärkyä	labelled	FALSE	Harvoin tai ei lainkaan=1,Noin kerran kuussa=2,Noin kerran viikossa=3,Lähes joka päivä=4	110	1055	1165	4	1: 411, 2: 327, 3: 246, NA: 110	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Harvoin tai ei lainkaan: 1
Noin kerran kuussa: 2
Noin kerran viikossa: 3
Lähes joka päivä: 4

symptom_tirednessFaintness_T1

Kys0038.1: Väsymystä tai heikotusta

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

107 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
symptom_tirednessFaintness_T1	Kys0038.1: Väsymystä tai heikotusta	labelled	FALSE	Harvoin tai ei lainkaan=1,Noin kerran kuussa=2,Noin kerran viikossa=3,Lähes joka päivä=4	107	1058	1165	4	1: 312, 2: 304, 3: 283, 4: 159	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Harvoin tai ei lainkaan: 1
Noin kerran kuussa: 2
Noin kerran viikossa: 3
Lähes joka päivä: 4

sitBreaks_T1

Keskimääräiset ylösnousut päivässä (T1)

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

452 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist	format.spss	display_width
sitBreaks_T1	Keskimääräiset ylösnousut päivässä (T1)	numeric	452	713	1165	28.16	11.08	7.14	19.83	26.8	35.33	65.86	<U+	2586><	U+2585> F8.2 0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

paLastweek_T1

Kys0046.1: Yhteensä - Tuntia:

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

83 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
paLastweek_T1	Kys0046.1: Yhteensä - Tuntia:	labelled	FALSE	0=1,1=2,2=3,3=4,4=5,5=6,6=7,7=8,8=9,9=10,10=11,11=12,12=13,13=14,14=15,15=16,16=17,17=18,18=19,19=20,20=21,21=22,22=23,23=24,24=25,25=26,26=27,27=28,28=29,29=30,30=31,31=32,32=33,33=34,34=35,35=36,36=37,37=38,38=39,39=40,40=41,41=42,42=43,43=44,44=45,45=46,46=47,47=48,48=49,49=50,50=51,51=52,52=53,53=54,54=55,55=56,56=57,57=58,58=59,59=60,60=61	83	1082	1165	60	60: 126, 150: 89, 180: 88, 120: 86	F2.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

big5agreeableness_T1

Kys0155.1: … sympaattinen ja ystävällinen

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

104 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
big5agreeableness_T1	Kys0155.1: … sympaattinen ja ystävällinen	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	104	1061	1165	7	7: 315, 6: 292, 5: 204, 4: 166	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

big5conscientiousness_T1

Kys0151.1: … luotettava ja saan tehtyä ne asiat, jotka lupaan tehdä

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

106 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
big5conscientiousness_T1	Kys0151.1: … luotettava ja saan tehtyä ne asiat, jotka lupaan tehdä	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	106	1059	1165	7	6: 314, 7: 273, 5: 204, 4: 161	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

big5extraversion_T1

Kys0149.1: … ulospäin suuntautunut, innostunut asioista

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

102 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
big5extraversion_T1	Kys0149.1: … ulospäin suuntautunut, innostunut asioista	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	102	1063	1165	7	7: 245, 6: 221, 4: 218, 5: 184	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

big5neuroticism_T1

Kys0152.1: … välillä ahdistunut ja hermostun helposti

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

101 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
big5neuroticism_T1	Kys0152.1: … välillä ahdistunut ja hermostun helposti	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	101	1064	1165	7	4: 222, 2: 167, 5: 166, 7: 151	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

big5openness_T1

Kys0153.1: … avoin uusille kokemuksille (pidän uusien asioiden tekemisestä)

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

103 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
big5openness_T1	Kys0153.1: … avoin uusille kokemuksille (pidän uusien asioiden tekemisestä)	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	103	1062	1165	7	7: 309, 6: 241, 5: 203, 4: 179	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_agrbct_T1

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

94 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_agrbct_T1	numeric	94	1071	1165	3.11	1.33	1	2	3.1	4.05	6

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_amotivation_T1

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

93 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_amotivation_T1	numeric	93	1072	1165	1.54	0.82	1	1	1	2	5

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_autonomous_T1

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

87 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_autonomous_T1	numeric	87	1078	1165	3.41	1.05	1	2.69	3.44	4.22	5

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_controlled_T1

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

92 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_controlled_T1	numeric	92	1073	1165	1.84	0.82	1	1	1.6	2.4	5

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_dnorm_T1

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

92 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_dnorm_T1	numeric	92	1073	1165	4.4	1.58	1	3.5	4.5	5.5	7

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_frqbct_T1

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

95 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_frqbct_T1	numeric	95	1070	1165	2.53	1.15	1	1.56	2.33	3.22	6.11

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_goal_T1

Kys0147.1: Onko sinulla tällä hetkellä liikuntatavoite?

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

104 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_goal_T1	Kys0147.1: Onko sinulla tällä hetkellä liikuntatavoite?	labelled	FALSE	Kyllä (kerro lyhyesti, mikä tämänhetkinen liikuntatavoittees=0,Ei=1	104	1061	1165	2	1: 592, 0: 469, NA: 104	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Kyllä (kerro lyhyesti, mikä tämänhetkinen liikuntatavoittees: 0
Ei: 1

PA_inorm_T1

Kys0108.1: Vanhempani haluaisivat minun liikkuvan säännöllisesti, vähintään 1,5 tuntia viik

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

92 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_inorm_T1	Kys0108.1: Vanhempani haluaisivat minun liikkuvan säännöllisesti, vähintään 1,5 tuntia viik	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,3=3,4=4,5=5,6=6,Pitää täysin paikkansa7=7	92	1073	1165	7	7: 306, 4: 219, 6: 136, 3: 117	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_intention_T1

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

92 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_intention_T1	numeric	92	1073	1165	5.38	1.85	1	4	6	7	7

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_outcomeExpectations_T1

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

87 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_outcomeExpectations_T1	numeric	87	1078	1165	4.59	0.91	1	4	4.67	5.25	7

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_opportunities_T1

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

90 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_opportunities_T1	numeric	90	1075	1165	5.12	0.93	1	4.5	5.12	5.75	7

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_pbc_T1

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

94 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_pbc_T1	numeric	94	1071	1165	5.33	1.28	1	4.33	5.33	6.33	7

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_selfefficacy_T1

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

94 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_selfefficacy_T1	numeric	94	1071	1165	5.22	1.3	1	4	5	6.5	7

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

SB_dnorm_T1

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

103 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
SB_dnorm_T1	numeric	103	1062	1165	3.23	1.45	1	2	4	4	7

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

SB_inorm_T1

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

101 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
SB_inorm_T1	numeric	101	1064	1165	4	1.25	1	3.5	4	4.5	7

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

SB_intention_T1

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

101 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
SB_intention_T1	numeric	101	1064	1165	3.71	1.62	1	2.5	4	5	7

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

SB_outcomeExpectations_T1

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

101 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
SB_outcomeExpectations_T1	numeric	101	1064	1165	4.41	1.05	1	4	4.43	5	7

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

SB_sePbc_T1

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

101 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
SB_sePbc_T1	numeric	101	1064	1165	4.95	1.26	1	4	5	5.8	7

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

symptom_T1

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

81 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
symptom_T1	numeric	81	1084	1165	1.95	0.67	1	1.38	1.88	2.38	4

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_actionplan_T1

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

92 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_actionplan_T1	numeric	92	1073	1165	2.76	0.93	1	2.25	3	3.5	4

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_copingplan_T1

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

92 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_copingplan_T1	numeric	92	1073	1165	2.5	0.87	1	2	2.75	3	4

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_actplan_01_T3

Kys0115.3: … milloin liikkua

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

243 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_actplan_01_T3	Kys0115.3: … milloin liikkua	labelled	FALSE	Ei pidä paikkaansa1=1,Ei pidä enimmäkseen paikkaansa2=2,Pitää enimmäkseen paikkansa3=3,Pitää täysin paikkansa4=4	243	922	1165	4	3: 364, NA: 243, 2: 198, 1: 182	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä paikkaansa1: 1
Ei pidä enimmäkseen paikkaansa2: 2
Pitää enimmäkseen paikkansa3: 3
Pitää täysin paikkansa4: 4

PA_actplan_02_T3

Kys0116.3: … missä liikkua

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

245 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_actplan_02_T3	Kys0116.3: … missä liikkua	labelled	FALSE	Ei pidä paikkaansa1=1,Ei pidä enimmäkseen paikkaansa2=2,Pitää enimmäkseen paikkansa3=3,Pitää täysin paikkansa4=4	245	920	1165	4	3: 374, NA: 245, 4: 241, 2: 153	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä paikkaansa1: 1
Ei pidä enimmäkseen paikkaansa2: 2
Pitää enimmäkseen paikkansa3: 3
Pitää täysin paikkansa4: 4

PA_actplan_03_T3

Kys0117.3: … kuinka liikkua

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

248 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_actplan_03_T3	Kys0117.3: … kuinka liikkua	labelled	FALSE	Ei pidä paikkaansa1=1,Ei pidä enimmäkseen paikkaansa2=2,Pitää enimmäkseen paikkansa3=3,Pitää täysin paikkansa4=4	248	917	1165	4	3: 396, NA: 248, 4: 232, 1: 146	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä paikkaansa1: 1
Ei pidä enimmäkseen paikkaansa2: 2
Pitää enimmäkseen paikkansa3: 3
Pitää täysin paikkansa4: 4

PA_actplan_04_T3

Kys0118.3: … kuinka usein liikkua

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

244 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_actplan_04_T3	Kys0118.3: … kuinka usein liikkua	labelled	FALSE	Ei pidä paikkaansa1=1,Ei pidä enimmäkseen paikkaansa2=2,Pitää enimmäkseen paikkansa3=3,Pitää täysin paikkansa4=4	244	921	1165	4	3: 382, NA: 244, 4: 215, 2: 176	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä paikkaansa1: 1
Ei pidä enimmäkseen paikkaansa2: 2
Pitää enimmäkseen paikkansa3: 3
Pitää täysin paikkansa4: 4

PA_agrbct_01_T3

Kys0128.3: Olen asettanut itselleni liikuntatavoitteita.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

237 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_agrbct_01_T3	Kys0128.3: Olen asettanut itselleni liikuntatavoitteita.	labelled	FALSE	Ei pidä lainkaan paikkaansa0=1,1=2,2=3,3=4,4=5,Pitää täysin paikkansa5=6	237	928	1165	6	NA: 237, 6: 216, 4: 187, 1: 163	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa0: 1
1: 2
2: 3
3: 4
4: 5
Pitää täysin paikkansa5: 6

PA_agrbct_02_T3

Kys0129.3: Olen itse tehnyt tarkan suunnitelman (mitä, missä, milloin) omaehtoisen liikun

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

240 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_agrbct_02_T3	Kys0129.3: Olen itse tehnyt tarkan suunnitelman (mitä, missä, milloin) omaehtoisen liikun	labelled	FALSE	Ei pidä lainkaan paikkaansa0=1,1=2,2=3,3=4,4=5,Pitää täysin paikkansa5=6	240	925	1165	6	NA: 240, 1: 233, 4: 165, 6: 156	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa0: 1
1: 2
2: 3
3: 4
4: 5
Pitää täysin paikkansa5: 6

PA_agrbct_03_T3

Kys0130.3: Minulla on liikuntasuunnitelma, jonka joku muu, esim. liikuntaseurani, on tehnyt

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

239 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_agrbct_03_T3	Kys0130.3: Minulla on liikuntasuunnitelma, jonka joku muu, esim. liikuntaseurani, on tehnyt	labelled	FALSE	Ei pidä lainkaan paikkaansa0=1,1=2,2=3,3=4,4=5,Pitää täysin paikkansa5=6	239	926	1165	6	1: 409, NA: 239, 6: 127, 3: 124	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa0: 1
1: 2
2: 3
3: 4
4: 5
Pitää täysin paikkansa5: 6

PA_agrbct_04_T3

Kys0131.3: Minulla on tapa, jolla muistutan itseäni liikuntasuunnitelmastani, esim. kirjoit

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

238 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_agrbct_04_T3	Kys0131.3: Minulla on tapa, jolla muistutan itseäni liikuntasuunnitelmastani, esim. kirjoit	labelled	FALSE	Ei pidä lainkaan paikkaansa0=1,1=2,2=3,3=4,4=5,Pitää täysin paikkansa5=6	238	927	1165	6	1: 355, NA: 238, 4: 147, 3: 138	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa0: 1
1: 2
2: 3
3: 4
4: 5
Pitää täysin paikkansa5: 6

PA_agrbct_05_T3

Kys0132.3: Olen pilkkonut laajempia liikuntatavoitteitani pienempiin osatavoitteisiin.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

239 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_agrbct_05_T3	Kys0132.3: Olen pilkkonut laajempia liikuntatavoitteitani pienempiin osatavoitteisiin.	labelled	FALSE	Ei pidä lainkaan paikkaansa0=1,1=2,2=3,3=4,4=5,Pitää täysin paikkansa5=6	239	926	1165	6	1: 305, NA: 239, 3: 171, 4: 159	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa0: 1
1: 2
2: 3
3: 4
4: 5
Pitää täysin paikkansa5: 6

PA_agrbct_06_T3

Kys0133.3: Olen kokeillut minulle uusia tapoja liikkua.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

248 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_agrbct_06_T3	Kys0133.3: Olen kokeillut minulle uusia tapoja liikkua.	labelled	FALSE	Ei pidä lainkaan paikkaansa0=1,1=2,2=3,3=4,4=5,Pitää täysin paikkansa5=6	248	917	1165	6	NA: 248, 1: 223, 4: 192, 3: 151	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa0: 1
1: 2
2: 3
3: 4
4: 5
Pitää täysin paikkansa5: 6

PA_agrbct_07_T3

Kys0134.3: Olen pohtinut, millaiset vaikeat tilanteet tai esteet estävät minua toteuttamast

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

248 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_agrbct_07_T3	Kys0134.3: Olen pohtinut, millaiset vaikeat tilanteet tai esteet estävät minua toteuttamast	labelled	FALSE	Ei pidä lainkaan paikkaansa0=1,1=2,2=3,3=4,4=5,Pitää täysin paikkansa5=6	248	917	1165	6	NA: 248, 1: 223, 3: 184, 4: 176	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa0: 1
1: 2
2: 3
3: 4
4: 5
Pitää täysin paikkansa5: 6

PA_agrbct_08_T3

Kys0135.3: Olen suunnitellut tapoja ylittää liikunnan harrastamisen esteitä.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

242 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_agrbct_08_T3	Kys0135.3: Olen suunnitellut tapoja ylittää liikunnan harrastamisen esteitä.	labelled	FALSE	Ei pidä lainkaan paikkaansa0=1,1=2,2=3,3=4,4=5,Pitää täysin paikkansa5=6	242	923	1165	6	NA: 242, 1: 230, 4: 197, 3: 177	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa0: 1
1: 2
2: 3
3: 4
4: 5
Pitää täysin paikkansa5: 6

PA_agrbct_09_T3

Kys0136.3: Olen miettinyt, miten liikunta sopii omaan minäkuvaani.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

240 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_agrbct_09_T3	Kys0136.3: Olen miettinyt, miten liikunta sopii omaan minäkuvaani.	labelled	FALSE	Ei pidä lainkaan paikkaansa0=1,1=2,2=3,3=4,4=5,Pitää täysin paikkansa5=6	240	925	1165	6	NA: 240, 4: 191, 1: 180, 6: 170	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa0: 1
1: 2
2: 3
3: 4
4: 5
Pitää täysin paikkansa5: 6

PA_agrbct_10_T3

Kys0137.3: Olen pyrkinyt löytämään tapoja liikkua siten, että se ei häiritse vaan tukee mui

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

244 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_agrbct_10_T3	Kys0137.3: Olen pyrkinyt löytämään tapoja liikkua siten, että se ei häiritse vaan tukee mui	labelled	FALSE	Ei pidä lainkaan paikkaansa0=1,1=2,2=3,3=4,4=5,Pitää täysin paikkansa5=6	244	921	1165	6	NA: 244, 4: 206, 1: 190, 3: 167	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa0: 1
1: 2
2: 3
3: 4
4: 5
Pitää täysin paikkansa5: 6

PA_amotivation_01_T3

Kys0082.3: En ymmärrä, miksi minun pitäisi liikkua vapaa-ajallani.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

244 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_amotivation_01_T3	Kys0082.3: En ymmärrä, miksi minun pitäisi liikkua vapaa-ajallani.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	244	921	1165	5	1: 644, NA: 244, 3: 117, 2: 110	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_amotivation_02_T3

Kys0086.3: En näe mitään syytä liikkua vapaa-ajallani.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

246 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_amotivation_02_T3	Kys0086.3: En näe mitään syytä liikkua vapaa-ajallani.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	246	919	1165	5	1: 628, NA: 246, 2: 122, 3: 116	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_amotivation_03_T3

Kys0096.3: En näe, mitä järkeä on liikkua vapaa-ajalla.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

245 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_amotivation_03_T3	Kys0096.3: En näe, mitä järkeä on liikkua vapaa-ajalla.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	245	920	1165	5	1: 574, NA: 245, 3: 140, 2: 137	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_amotivation_04_T3

Kys0097.3: Mielestäni liikkuminen on ajanhukkaa.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

236 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_amotivation_04_T3	Kys0097.3: Mielestäni liikkuminen on ajanhukkaa.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	236	929	1165	5	1: 638, NA: 236, 2: 121, 3: 107	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_copplan_01_T3

Kys0119.3: … mitä tehdä silloin, kun jokin sotkee suunnitelmani

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

234 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_copplan_01_T3	Kys0119.3: … mitä tehdä silloin, kun jokin sotkee suunnitelmani	labelled	FALSE	Ei pidä paikkaansa1=1,Ei pidä enimmäkseen paikkaansa2=2,Pitää enimmäkseen paikkansa3=3,Pitää täysin paikkansa4=4	234	931	1165	4	3: 322, 2: 243, NA: 234, 1: 224	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä paikkaansa1: 1
Ei pidä enimmäkseen paikkaansa2: 2
Pitää enimmäkseen paikkansa3: 3
Pitää täysin paikkansa4: 4

PA_copplan_02_T3

Kys0120.3: … kuinka selviytyä repsahduksista

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

236 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_copplan_02_T3	Kys0120.3: … kuinka selviytyä repsahduksista	labelled	FALSE	Ei pidä paikkaansa1=1,Ei pidä enimmäkseen paikkaansa2=2,Pitää enimmäkseen paikkansa3=3,Pitää täysin paikkansa4=4	236	929	1165	4	3: 317, 2: 263, NA: 236, 1: 207	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä paikkaansa1: 1
Ei pidä enimmäkseen paikkaansa2: 2
Pitää enimmäkseen paikkansa3: 3
Pitää täysin paikkansa4: 4

PA_copplan_03_T3

Kys0121.3: … kuinka pysyä suunnitelmissa vaikeissakin tilanteissa

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

237 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_copplan_03_T3	Kys0121.3: … kuinka pysyä suunnitelmissa vaikeissakin tilanteissa	labelled	FALSE	Ei pidä paikkaansa1=1,Ei pidä enimmäkseen paikkaansa2=2,Pitää enimmäkseen paikkansa3=3,Pitää täysin paikkansa4=4	237	928	1165	4	3: 331, 2: 247, NA: 237, 1: 207	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä paikkaansa1: 1
Ei pidä enimmäkseen paikkaansa2: 2
Pitää enimmäkseen paikkansa3: 3
Pitää täysin paikkansa4: 4

PA_copplan_04_T3

Kys0122.3: … kuinka hyödyntää hyviä tilaisuuksia liikkumiseen

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

243 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_copplan_04_T3	Kys0122.3: … kuinka hyödyntää hyviä tilaisuuksia liikkumiseen	labelled	FALSE	Ei pidä paikkaansa1=1,Ei pidä enimmäkseen paikkaansa2=2,Pitää enimmäkseen paikkansa3=3,Pitää täysin paikkansa4=4	243	922	1165	4	3: 380, NA: 243, 4: 188, 2: 184	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä paikkaansa1: 1
Ei pidä enimmäkseen paikkaansa2: 2
Pitää enimmäkseen paikkansa3: 3
Pitää täysin paikkansa4: 4

PA_dnormparents_02_T3

Kys0107.3: Vanhempani liikkuvat säännöllisesti, vähintään 1,5 tuntia viikoittain

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

238 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_dnormparents_02_T3	Kys0107.3: Vanhempani liikkuvat säännöllisesti, vähintään 1,5 tuntia viikoittain	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,3=3,4=4,5=5,6=6,Pitää täysin paikkansa7=7	238	927	1165	7	NA: 238, 7: 193, 4: 192, 3: 135	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_dnorm_01_T3

Kys0106.3: Suurin osa ystävistäni liikkuu säännöllisesti, vähintään 1,5 tuntia viikoittain

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

234 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_dnorm_01_T3	Kys0106.3: Suurin osa ystävistäni liikkuu säännöllisesti, vähintään 1,5 tuntia viikoittain	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,3=3,4=4,5=5,6=6,Pitää täysin paikkansa7=7	234	931	1165	7	NA: 234, 4: 233, 7: 181, 3: 143	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_controlled_01_T3

Kys0080.3: koska muut ihmiset sanovat, että minun pitää liikkua.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

237 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_controlled_01_T3	Kys0080.3: koska muut ihmiset sanovat, että minun pitää liikkua.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	237	928	1165	5	1: 554, NA: 237, 3: 170, 2: 145	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_controlled_02_T3

Kys0081.3: koska muut ihmiset ovat tyytymättömiä minuun, jos en liiku.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

239 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_controlled_02_T3	Kys0081.3: koska muut ihmiset ovat tyytymättömiä minuun, jos en liiku.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	239	926	1165	5	1: 611, NA: 239, 2: 146, 3: 115	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_controlled_03_T3

Kys0083.3: koska kaverini ja perheeni painostavat minua liikkumaan.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

244 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_controlled_03_T3	Kys0083.3: koska kaverini ja perheeni painostavat minua liikkumaan.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	244	921	1165	5	1: 604, NA: 244, 3: 127, 2: 120	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_frqbct_01_T3

Kys0138.3: Olen muistuttanut mieleeni myös vapaa-ajallani, millaisia myönteisiä seurauksia

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

237 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_frqbct_01_T3	Kys0138.3: Olen muistuttanut mieleeni myös vapaa-ajallani, millaisia myönteisiä seurauksia	labelled	FALSE	En kertaakaan0=1,Kerran1=2,Kahdesti2=3,Viikoittain3=4,Noin joka toinen päivä4=5,Päivittäin5=6	237	928	1165	6	4: 252, NA: 237, 3: 183, 6: 137	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

En kertaakaan0: 1
Kerran1: 2
Kahdesti2: 3
Viikoittain3: 4
Noin joka toinen päivä4: 5
Päivittäin5: 6

PA_frqbct_02_T3

Kys0139.3: Olen seurannut liikkumistani merkitsemällä liikuntakerrat paperiseen liikkumispä

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

243 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_frqbct_02_T3	Kys0139.3: Olen seurannut liikkumistani merkitsemällä liikuntakerrat paperiseen liikkumispä	labelled	FALSE	En kertaakaan0=1,Kerran1=2,Kahdesti2=3,Viikoittain3=4,Noin joka toinen päivä4=5,Päivittäin5=6	243	922	1165	6	1: 481, NA: 243, 4: 121, 3: 118	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

En kertaakaan0: 1
Kerran1: 2
Kahdesti2: 3
Viikoittain3: 4
Noin joka toinen päivä4: 5
Päivittäin5: 6

PA_frqbct_03_T3

Kys0140.3: Olen seurannut liikkumistani käyttämällä älypuhelinta, esim. Moves-appia.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

243 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_frqbct_03_T3	Kys0140.3: Olen seurannut liikkumistani käyttämällä älypuhelinta, esim. Moves-appia.	labelled	FALSE	En kertaakaan0=1,Kerran1=2,Kahdesti2=3,Viikoittain3=4,Noin joka toinen päivä4=5,Päivittäin5=6	243	922	1165	6	1: 497, NA: 243, 3: 125, 4: 121	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

En kertaakaan0: 1
Kerran1: 2
Kahdesti2: 3
Viikoittain3: 4
Noin joka toinen päivä4: 5
Päivittäin5: 6

PA_frqbct_04_T3

Kys0141.3: Käytän muistivihjeitä, joiden avulla muistan toteuttaa liikunta-aikomukseni.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

246 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_frqbct_04_T3	Kys0141.3: Käytän muistivihjeitä, joiden avulla muistan toteuttaa liikunta-aikomukseni.	labelled	FALSE	En kertaakaan0=1,Kerran1=2,Kahdesti2=3,Viikoittain3=4,Noin joka toinen päivä4=5,Päivittäin5=6	246	919	1165	6	1: 524, NA: 246, 3: 115, 4: 88	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

En kertaakaan0: 1
Kerran1: 2
Kahdesti2: 3
Viikoittain3: 4
Noin joka toinen päivä4: 5
Päivittäin5: 6

PA_frqbct_05_T3

Kys0142.3: Olen verrannut toteutunutta liikuntaani asettamaani liikuntatavoitteeseen.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

250 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_frqbct_05_T3	Kys0142.3: Olen verrannut toteutunutta liikuntaani asettamaani liikuntatavoitteeseen.	labelled	FALSE	En kertaakaan0=1,Kerran1=2,Kahdesti2=3,Viikoittain3=4,Noin joka toinen päivä4=5,Päivittäin5=6	250	915	1165	6	1: 360, NA: 250, 4: 162, 3: 155	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

En kertaakaan0: 1
Kerran1: 2
Kahdesti2: 3
Viikoittain3: 4
Noin joka toinen päivä4: 5
Päivittäin5: 6

PA_frqbct_06_T3

Kys0143.3: Olen miettinyt, mitkä liikunnan harrastamisen syyt ovat minulle itselleni tärkei

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

249 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_frqbct_06_T3	Kys0143.3: Olen miettinyt, mitkä liikunnan harrastamisen syyt ovat minulle itselleni tärkei	labelled	FALSE	En kertaakaan0=1,Kerran1=2,Kahdesti2=3,Viikoittain3=4,Noin joka toinen päivä4=5,Päivittäin5=6	249	916	1165	6	NA: 249, 4: 207, 1: 190, 3: 155	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

En kertaakaan0: 1
Kerran1: 2
Kahdesti2: 3
Viikoittain3: 4
Noin joka toinen päivä4: 5
Päivittäin5: 6

PA_frqbct_07_T3

Kys0144.3: Olen tehnyt muutoksia kotiini (esim. huoneeseeni tai tietokoneelleni), jotta lii

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

243 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_frqbct_07_T3	Kys0144.3: Olen tehnyt muutoksia kotiini (esim. huoneeseeni tai tietokoneelleni), jotta lii	labelled	FALSE	En kertaakaan0=1,Kerran1=2,Kahdesti2=3,Viikoittain3=4,Noin joka toinen päivä4=5,Päivittäin5=6	243	922	1165	6	1: 439, NA: 243, 3: 136, 4: 122	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

En kertaakaan0: 1
Kerran1: 2
Kahdesti2: 3
Viikoittain3: 4
Noin joka toinen päivä4: 5
Päivittäin5: 6

PA_frqbct_08_T3

Kys0145.3: Olen pyytänyt kavereiltani tai perheeltäni tukea liikuntatavoitteideni saavuttam

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

243 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_frqbct_08_T3	Kys0145.3: Olen pyytänyt kavereiltani tai perheeltäni tukea liikuntatavoitteideni saavuttam	labelled	FALSE	En kertaakaan0=1,Kerran1=2,Kahdesti2=3,Viikoittain3=4,Noin joka toinen päivä4=5,Päivittäin5=6	243	922	1165	6	1: 384, NA: 243, 3: 148, 4: 147	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

En kertaakaan0: 1
Kerran1: 2
Kahdesti2: 3
Viikoittain3: 4
Noin joka toinen päivä4: 5
Päivittäin5: 6

PA_frqbct_09_T3

Kys0146.3: Jos en ole saavuttanut liikuntatavoitettani, olen arvioinut, mikä meni pieleen.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

252 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_frqbct_09_T3	Kys0146.3: Jos en ole saavuttanut liikuntatavoitettani, olen arvioinut, mikä meni pieleen.	labelled	FALSE	En kertaakaan0=1,Kerran1=2,Kahdesti2=3,Viikoittain3=4,Noin joka toinen päivä4=5,Päivittäin5=6,Saavutin tavoitteeni6=7	252	913	1165	7	1: 297, NA: 252, 4: 169, 3: 130	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

En kertaakaan0: 1
Kerran1: 2
Kahdesti2: 3
Viikoittain3: 4
Noin joka toinen päivä4: 5
Päivittäin5: 6
Saavutin tavoitteeni6: 7

PA_goal_01_T3

Kys0147.3: Onko sinulla tällä hetkellä liikuntatavoite?

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

257 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_goal_01_T3	Kys0147.3: Onko sinulla tällä hetkellä liikuntatavoite?	labelled	FALSE	Kyllä (kerro lyhyesti, mikä tämänhetkinen liikuntatavoittees=0,Ei=1	257	908	1165	2	1: 554, 0: 354, NA: 257	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Kyllä (kerro lyhyesti, mikä tämänhetkinen liikuntatavoittees: 0
Ei: 1

PA_autonomous_01_T3

Kys0087.3: koska minusta on tärkeää nähdä vaivaa säännöllisen liikunnan eteen.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

241 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_autonomous_01_T3	Kys0087.3: koska minusta on tärkeää nähdä vaivaa säännöllisen liikunnan eteen.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	241	924	1165	5	3: 279, NA: 241, 4: 193, 5: 178	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_autonomous_02_T3

Kys0088.3: koska arvostan liikunnasta saamaani hyötyä.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

240 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_autonomous_02_T3	Kys0088.3: koska arvostan liikunnasta saamaani hyötyä.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	240	925	1165	5	5: 334, NA: 240, 4: 225, 3: 212	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_autonomous_03_T3

Kys0090.3: koska minulle on tärkeää liikkua säännöllisesti.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

244 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_autonomous_03_T3	Kys0090.3: koska minulle on tärkeää liikkua säännöllisesti.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	244	921	1165	5	3: 255, NA: 244, 5: 236, 4: 212	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_inorm_01_T3

Kys0108.3: Vanhempani haluaisivat minun liikkuvan säännöllisesti, vähintään 1,5 tuntia viik

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

238 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_inorm_01_T3	Kys0108.3: Vanhempani haluaisivat minun liikkuvan säännöllisesti, vähintään 1,5 tuntia viik	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,3=3,4=4,5=5,6=6,Pitää täysin paikkansa7=7	238	927	1165	7	4: 244, NA: 238, 7: 235, 5: 102	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_autonomous_04_T3

Kys0089.3: koska se sopii yhteen elämäntavoitteideni kanssa.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

239 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_autonomous_04_T3	Kys0089.3: koska se sopii yhteen elämäntavoitteideni kanssa.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	239	926	1165	5	3: 305, NA: 239, 5: 221, 4: 199	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_autonomous_05_T3

Kys0092.3: …koska liikunta sopii yhteen arvojeni kanssa.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

239 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_autonomous_05_T3	Kys0092.3: …koska liikunta sopii yhteen arvojeni kanssa.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	239	926	1165	5	3: 290, NA: 239, 4: 219, 5: 214	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_autonomous_06_T3

Kys0094.3: koska liikunta on keskeinen osa sitä, kuka olen.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

241 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_autonomous_06_T3	Kys0094.3: koska liikunta on keskeinen osa sitä, kuka olen.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	241	924	1165	5	3: 268, NA: 241, 5: 204, 4: 165	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_intention_01_T3

Kys0113.3: Aion liikkua säännöllisesti viikoittain vähintään 1,5 tuntia seuraavan kuukauden

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

245 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_intention_01_T3	Kys0113.3: Aion liikkua säännöllisesti viikoittain vähintään 1,5 tuntia seuraavan kuukauden	labelled	FALSE	Epätodennäköistä1=1,2=2,3=3,4=4,5=5,6=6,Todennäköistä7=7	245	920	1165	7	7: 369, NA: 245, 4: 162, 5: 107	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Epätodennäköistä1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Todennäköistä7: 7

PA_intention_02_T3

Kys0114.3: Aion liikkua säännöllisesti viikoittain vähintään 1,5 tuntia seuraavan kuukauden

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

241 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_intention_02_T3	Kys0114.3: Aion liikkua säännöllisesti viikoittain vähintään 1,5 tuntia seuraavan kuukauden	labelled	FALSE	Ehdottomasti en1=1,2=2,3=3,4=4,5=5,6=6,Ehdottomasti kyllä7=7	241	924	1165	7	7: 373, NA: 241, 4: 170, 5: 110	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ehdottomasti en1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Ehdottomasti kyllä7: 7

PA_autonomous_07_T3

Kys0091.3: koska tunnen iloa ja tyytyväisyyttä, kun liikun.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

241 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_autonomous_07_T3	Kys0091.3: koska tunnen iloa ja tyytyväisyyttä, kun liikun.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	241	924	1165	5	5: 285, 4: 267, NA: 241, 3: 223	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_autonomous_08_T3

Kys0093.3: koska liikkuminen on hauskaa.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

242 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_autonomous_08_T3	Kys0093.3: koska liikkuminen on hauskaa.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	242	923	1165	5	5: 279, 4: 273, NA: 242, 3: 235	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_autonomous_09_T3

Kys0095.3: koska nautin liikuntahetkistä.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

247 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_autonomous_09_T3	Kys0095.3: koska nautin liikuntahetkistä.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	247	918	1165	5	3: 264, 5: 250, 4: 247, NA: 247	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_controlled_04_T3

Kys0084.3: koska tunnen syyllisyyttä, jos en liiku.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

244 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_controlled_04_T3	Kys0084.3: koska tunnen syyllisyyttä, jos en liiku.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	244	921	1165	5	1: 372, NA: 244, 3: 234, 4: 125	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_controlled_05_T3

Kys0085.3: koska tunnen itseni epäonnistuneeksi, jos en ole liikkunut vähään aikaan.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

239 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_controlled_05_T3	Kys0085.3: koska tunnen itseni epäonnistuneeksi, jos en ole liikkunut vähään aikaan.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	239	926	1165	5	1: 335, NA: 239, 3: 217, 2: 140	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_outcomeExpectations_01_T3

Kys0068.3: Se saisi minut hyvälle tuulelle

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

233 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_outcomeExpectations_01_T3	Kys0068.3: Se saisi minut hyvälle tuulelle	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	233	932	1165	7	7: 338, NA: 233, 4: 171, 6: 162	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_outcomeExpectations_03_T3

Kys0070.3: Se auttaisi pitämään painoni kurissa

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

239 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_outcomeExpectations_03_T3	Kys0070.3: Se auttaisi pitämään painoni kurissa	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	239	926	1165	7	7: 298, NA: 239, 4: 208, 6: 153	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_outcomeExpectations_04_T3

Kys0071.3: Se auttaisi kasvattamaan lihasmassaa

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

236 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_outcomeExpectations_04_T3	Kys0071.3: Se auttaisi kasvattamaan lihasmassaa	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	236	929	1165	7	7: 335, NA: 236, 6: 189, 5: 164	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_outcomeExpectations_05_T3

Kys0072.3: Se parantaisi kykyäni tehdä töitä ja päivittäisiä askareitani

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

235 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_outcomeExpectations_05_T3	Kys0072.3: Se parantaisi kykyäni tehdä töitä ja päivittäisiä askareitani	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	235	930	1165	7	7: 248, NA: 235, 4: 207, 5: 202	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_outcomeExpectations_06_T3

Kys0073.3: Se auttaisi minua jaksamaan

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

237 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_outcomeExpectations_06_T3	Kys0073.3: Se auttaisi minua jaksamaan	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	237	928	1165	7	7: 282, NA: 237, 5: 196, 4: 180	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_outcomeExpectations_07_T3

Kys0074.3: Saisin sen avulla uusia kokemuksia

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

239 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_outcomeExpectations_07_T3	Kys0074.3: Saisin sen avulla uusia kokemuksia	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	239	926	1165	7	4: 247, NA: 239, 7: 202, 5: 186	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_outcomeExpectations_10_T3

Kys0077.3: Se auttaisi minua nukkumaan paremmin

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

237 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_outcomeExpectations_10_T3	Kys0077.3: Se auttaisi minua nukkumaan paremmin	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	237	928	1165	7	7: 294, NA: 237, 4: 190, 6: 190	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_outcomeExpectations_11_T3

Kys0078.3: Saisin sen avulla onnistumisen kokemuksia

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

238 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_outcomeExpectations_11_T3	Kys0078.3: Saisin sen avulla onnistumisen kokemuksia	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	238	927	1165	7	7: 272, NA: 238, 4: 222, 6: 171	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_outcomeExpectations_12_T3

Kys0079.3: Se tukisi itsetuntoani

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

243 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_outcomeExpectations_12_T3	Kys0079.3: Se tukisi itsetuntoani	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	243	922	1165	7	7: 298, NA: 243, 4: 212, 6: 157	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_outcomeExpectationsNegative_02_T3

Kys0069.3: Se veisi liikaa aikaa muilta elämäni tärkeiltä asioilta

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

238 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_outcomeExpectationsNegative_02_T3	Kys0069.3: Se veisi liikaa aikaa muilta elämäni tärkeiltä asioilta	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	238	927	1165	7	NA: 238, 4: 223, 1: 222, 2: 188	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_outcomeExpectationsNegative_08_T3

Kys0075.3: Se olisi stressaavaa ja henkisesti rasittavaa

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

234 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_outcomeExpectationsNegative_08_T3	Kys0075.3: Se olisi stressaavaa ja henkisesti rasittavaa	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	234	931	1165	7	1: 312, NA: 234, 2: 209, 4: 206	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_outcomeExpectationsNegative_09_T3

Kys0076.3: Se olisi ikävällä tavalla fyysisesti väsyttävää

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

239 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_outcomeExpectationsNegative_09_T3	Kys0076.3: Se olisi ikävällä tavalla fyysisesti väsyttävää	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	239	926	1165	7	1: 292, NA: 239, 2: 196, 4: 187	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_opportunities_01_T3

Kys0098.3: Minulla on riittävästi rahaa liikunnan harrastamiseen

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

235 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_opportunities_01_T3	Kys0098.3: Minulla on riittävästi rahaa liikunnan harrastamiseen	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Pitää täysin paikkansa7=7	235	930	1165	7	7: 275, NA: 235, 4: 207, 5: 111	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_opportunities_02_T3

Kys0099.3: Ympäristössäni on hyviä pyöräteitä ja lenkkipolkuja

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

235 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_opportunities_02_T3	Kys0099.3: Ympäristössäni on hyviä pyöräteitä ja lenkkipolkuja	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Pitää täysin paikkansa7=7	235	930	1165	7	7: 346, NA: 235, 6: 177, 5: 149	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_opportunities_04_T3

Kys0101.3: Lähistölläni on paljon hyviä liikuntapaikkoja (esim. urheiluhalleja, kuntosaleja

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

233 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_opportunities_04_T3	Kys0101.3: Lähistölläni on paljon hyviä liikuntapaikkoja (esim. urheiluhalleja, kuntosaleja	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Pitää täysin paikkansa7=7	233	932	1165	7	7: 356, NA: 233, 6: 168, 4: 159	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_opportunities_05_T3

Kys0102.3: Liikuntavälineiden puute ei ole este liikkumiselleni

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

235 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_opportunities_05_T3	Kys0102.3: Liikuntavälineiden puute ei ole este liikkumiselleni	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Pitää täysin paikkansa7=7	235	930	1165	7	7: 322, NA: 235, 4: 193, 6: 146	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_opportunities_07_T3

Kys0104.3: Minulla on paljon mahdollisuuksia harrastaa liikuntaa kotona

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

229 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_opportunities_07_T3	Kys0104.3: Minulla on paljon mahdollisuuksia harrastaa liikuntaa kotona	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Pitää täysin paikkansa7=7	229	936	1165	7	NA: 229, 4: 225, 7: 220, 5: 178	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_opportunitiesReverseCoded_03_T3

Kys0100.3: Minulla ei ole tarvitsemiani liikuntavälineitä

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

235 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_opportunitiesReverseCoded_03_T3	Kys0100.3: Minulla ei ole tarvitsemiani liikuntavälineitä	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Pitää täysin paikkansa7=7	235	930	1165	7	7: 293, NA: 235, 4: 230, 6: 141	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_opportunitiesReverseCoded_06_T3

Kys0103.3: Minulla on paljon kiireitä koulun, harrastusten ja/tai kaverien vuoksi

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

233 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_opportunitiesReverseCoded_06_T3	Kys0103.3: Minulla on paljon kiireitä koulun, harrastusten ja/tai kaverien vuoksi	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Pitää täysin paikkansa7=7	233	932	1165	7	NA: 233, 4: 228, 3: 157, 1: 147	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_pbc_01_T3

Kys0125.3: Voin itse täysin vaikuttaa siihen, liikunko säännöllisesti.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

232 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_pbc_01_T3	Kys0125.3: Voin itse täysin vaikuttaa siihen, liikunko säännöllisesti.	labelled	FALSE	Ei pidä lainkaan paikkaansa1=1,2=2,3=3,4=4,5=5,6=6,Pitää täysin paikkansa7=7	232	933	1165	7	7: 369, NA: 232, 5: 163, 4: 159	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_pbc_03_T3

Kys0127.3: Olen varma, että pystyisin voittamaan hankaluudet, jotka estävät minua liikkumas

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

235 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_pbc_03_T3	Kys0127.3: Olen varma, että pystyisin voittamaan hankaluudet, jotka estävät minua liikkumas	labelled	FALSE	Ei pidä lainkaan paikkaansa1=1,2=2,3=3,4=4,5=5,6=6,Pitää täysin paikkansa7=7	235	930	1165	7	NA: 235, 7: 231, 4: 227, 5: 163	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_pbcReverseCoded_02_T3

Kys0126.3: Liikkuminen säännöllisesti ei riipu täysin minusta.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

234 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_pbcReverseCoded_02_T3	Kys0126.3: Liikkuminen säännöllisesti ei riipu täysin minusta.	labelled	FALSE	Ei pidä lainkaan paikkaansa1=1,2=2,3=3,4=4,5=5,6=6,Pitää täysin paikkansa7=7	234	931	1165	7	NA: 234, 7: 206, 4: 195, 3: 135	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_selfefficacy_01_T3

Kys0123.3: Jos haluaisin, voisin liikkua säännöllisesti.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

234 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_selfefficacy_01_T3	Kys0123.3: Jos haluaisin, voisin liikkua säännöllisesti.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,4=4,5=5,6=6,Täysin samaa mieltä7=7	234	931	1165	7	7: 437, NA: 234, 5: 164, 4: 136	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_selfefficacyReverseCoded_02_T3

Kys0124.3: Liikkuminen säännöllisesti on minulle

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

229 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_selfefficacyReverseCoded_02_T3	Kys0124.3: Liikkuminen säännöllisesti on minulle	labelled	FALSE	Helppoa1=1,2=2,3=3,4=4,5=5,6=6,Vaikeaa7=7	229	936	1165	7	NA: 229, 4: 199, 7: 167, 3: 148	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Helppoa1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Vaikeaa7: 7

paAccelerometer_T3

Keskimääräinen reippaan ja rasittavan liikunnan (MVPA) minuutit päivässä (T3)

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

657 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist	format.spss	display_width
paAccelerometer_T3	Keskimääräinen reippaan ja rasittavan liikunnan (MVPA) minuutit päivässä (T3)	numeric	657	508	1165	180.85	52.53	47.48	144.48	180.5	212.97	372.14	<U+	2583><	U+2587> F8.2 0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

padaysLastweek_T3

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

221 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
padaysLastweek_T3	labelled	FALSE	0 (en yhtenäkään)=0,1=1,2=2,3=3,4=4,5=5,6=6,7=7	221	944	1165	8	3: 237, NA: 221, 2: 189, 4: 152	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

0 (en yhtenäkään): 0
1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
7: 7

pafreqUsually_T3

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

231 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
pafreqUsually_T3	labelled	FALSE	En voi vamman tai sairauden takia harrastaa liikuntaa=0,Harvemmin kuin kerran viikossa=1,1-2 kertaa viikossa=2,3 kertaa viikossa=3,4 kertaa viikossa=4,5 kertaa viikossa tai useammin=5	231	934	1165	6	2: 312, NA: 231, 3: 199, 1: 184	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

En voi vamman tai sairauden takia harrastaa liikuntaa: 0
Harvemmin kuin kerran viikossa: 1
1-2 kertaa viikossa: 2
3 kertaa viikossa: 3
4 kertaa viikossa: 4
5 kertaa viikossa tai useammin: 5

pahrsLastweek_T3

Kys0046.3: Yhteensä - Tuntia:

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

264 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
pahrsLastweek_T3	Kys0046.3: Yhteensä - Tuntia:	labelled	FALSE	0=1,1=2,2=3,3=4,4=5,5=6,6=7,7=8,8=9,9=10,10=11,11=12,12=13,13=14,14=15,15=16,16=17,17=18,18=19,19=20,20=21,21=22,22=23,23=24,24=25,25=26,26=27,27=28,28=29,29=30,30=31,31=32,32=33,33=34,34=35,35=36,36=37,37=38,38=39,39=40,40=41,41=42,42=43,43=44,44=45,45=46,46=47,47=48,48=49,49=50,50=51,51=52,52=53,53=54,54=55,55=56,56=57,57=58,58=59,59=60,60=61	264	901	1165	34	NA: 264, 2: 163, 3: 130, 4: 121	F2.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

pahrsUsually_T3

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

236 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
pahrsUsually_T3	labelled	FALSE	En yhtään=0,Noin puoli tuntia=1,Noin 1 tunnin=2,Noin 1,5 tuntia=3,Noin 2-3 tuntia=4,Noin 4-6 tuntia=5,Noin 7 tuntia tai enemmän=6	236	929	1165	7	NA: 236, 4: 196, 5: 170, 3: 156	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

En yhtään: 0
Noin puoli tuntia: 1
Noin 1 tunnin: 2
Noin 1,5 tuntia: 3
Noin 2-3 tuntia: 4
Noin 4-6 tuntia: 5
Noin 7 tuntia tai enemmän: 6

paminLastweek_T3

Kys0047.3: Yhteensä - Minuuttia:

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

440 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
paminLastweek_T3	Kys0047.3: Yhteensä - Minuuttia:	labelled	FALSE	0=1,30=2	440	725	1165	2	NA: 440, 2: 397, 1: 328	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

0: 1
30: 2

SB_dnorm_01_T3

Kys0178.3: yrittää rajoittaa omaa istumistaan KOULUPÄIVÄN aikana.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

249 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_dnorm_01_T3	Kys0178.3: yrittää rajoittaa omaa istumistaan KOULUPÄIVÄN aikana.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	249	916	1165	7	4: 367, NA: 249, 1: 215, 2: 102	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_dnorm_02_T3

Kys0179.3: yrittää rajoittaa omaa istumistaan VAPAA-AJALLA.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

255 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_dnorm_02_T3	Kys0179.3: yrittää rajoittaa omaa istumistaan VAPAA-AJALLA.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	255	910	1165	7	4: 394, NA: 255, 1: 163, 2: 93	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_inorm_01_T3

Kys0180.3: pitää hyväksyttävänä, että yritän rajoittaa omaa istumistani KOULUSSA.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

252 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_inorm_01_T3	Kys0180.3: pitää hyväksyttävänä, että yritän rajoittaa omaa istumistani KOULUSSA.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	252	913	1165	7	4: 423, NA: 252, 7: 115, 5: 101	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_inorm_02_T3

Kys0181.3: Suurin osa opettajistani hyväksyisi sen, jos rajoitan omaa istumistani KOULUSSA.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

257 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_inorm_02_T3	Kys0181.3: Suurin osa opettajistani hyväksyisi sen, jos rajoitan omaa istumistani KOULUSSA.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	257	908	1165	7	4: 382, NA: 257, 5: 137, 7: 110	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_intention_01_T3

Kys0187.3: Aion rajoittaa omaa istumistani seuraavan kuukauden aikana KOULUSSA.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

252 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_intention_01_T3	Kys0187.3: Aion rajoittaa omaa istumistani seuraavan kuukauden aikana KOULUSSA.	labelled	FALSE	Epätodennäköistä1=1,2=2,3=3,4=4,5=5,6=6,Todennäköistä7=7	252	913	1165	7	NA: 252, 4: 243, 1: 166, 3: 129	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Epätodennäköistä1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Todennäköistä7: 7

SB_intention_02_T3

Kys0188.3: Aion rajoittaa omaa istumistani seuraavan kuukauden aikana KOULUSSA.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

254 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_intention_02_T3	Kys0188.3: Aion rajoittaa omaa istumistani seuraavan kuukauden aikana KOULUSSA.	labelled	FALSE	Ehdottomasti en1=1,2=2,3=3,4=4,5=5,6=6,Ehdottomasti kyllä7=7	254	911	1165	7	4: 277, NA: 254, 3: 129, 5: 128	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ehdottomasti en1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Ehdottomasti kyllä7: 7

SB_intention_03_T3

Kys0189.3: Aion rajoittaa omaa istumistani seuraavan kuukauden aikana VAPAA-AJALLA.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

253 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_intention_03_T3	Kys0189.3: Aion rajoittaa omaa istumistani seuraavan kuukauden aikana VAPAA-AJALLA.	labelled	FALSE	Epätodennäköistä1=1,2=2,3=3,4=4,5=5,6=6,Todennäköistä7=7	253	912	1165	7	NA: 253, 4: 223, 5: 151, 7: 151	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Epätodennäköistä1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Todennäköistä7: 7

SB_intention_04_T3

Kys0190.3: Aion rajoittaa omaa istumistani seuraavan kuukauden aikana VAPAA-AJALLA.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

252 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_intention_04_T3	Kys0190.3: Aion rajoittaa omaa istumistani seuraavan kuukauden aikana VAPAA-AJALLA.	labelled	FALSE	Ehdottomasti en1=1,2=2,3=3,4=4,5=5,6=6,Ehdottomasti kyllä7=7	252	913	1165	7	NA: 252, 4: 249, 5: 163, 7: 143	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ehdottomasti en1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Ehdottomasti kyllä7: 7

SB_outcomeExpectationsNegative_01_T3

Kys0171.3: … oloni olisi epämukava.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

250 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_outcomeExpectationsNegative_01_T3	Kys0171.3: … oloni olisi epämukava.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	250	915	1165	7	4: 310, 1: 273, NA: 250, 2: 105	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_outcomeExpectations_02_T3

Kys0172.3: … virkistyisin ja jaksaisin paremmin.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

254 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_outcomeExpectations_02_T3	Kys0172.3: … virkistyisin ja jaksaisin paremmin.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	254	911	1165	7	NA: 254, 4: 253, 7: 207, 5: 200	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_outcomeExpectations_03_T3

Kys0173.3: keskittymiskykyni paranisi.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

256 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_outcomeExpectations_03_T3	Kys0173.3: keskittymiskykyni paranisi.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	256	909	1165	7	4: 268, NA: 256, 7: 201, 5: 190	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_outcomeExpectations_04_T3

Kys0174.3: niska-, hartia- ja selkäkivut sekä päänsäryt vähenisivät.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

253 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_outcomeExpectations_04_T3	Kys0174.3: niska-, hartia- ja selkäkivut sekä päänsäryt vähenisivät.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	253	912	1165	7	NA: 253, 4: 243, 7: 230, 5: 149	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_outcomeExpectations_05_T3

Kys0175.3: lihakseni eivät rappeutuisi.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

254 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_outcomeExpectations_05_T3	Kys0175.3: lihakseni eivät rappeutuisi.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	254	911	1165	7	4: 258, NA: 254, 7: 225, 5: 166	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_outcomeExpectations_06_T3

Kys0176.3: aivoni toimisivat paremmin.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

256 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_outcomeExpectations_06_T3	Kys0176.3: aivoni toimisivat paremmin.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	256	909	1165	7	4: 258, NA: 256, 7: 217, 6: 158	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_outcomeExpectationsNegative_07_T3

Kys0177.3: se häiritsisi asioiden tekemistä.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

252 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_outcomeExpectationsNegative_07_T3	Kys0177.3: se häiritsisi asioiden tekemistä.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	252	913	1165	7	4: 313, NA: 252, 1: 211, 2: 118	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_sePbc_01_T3

Kys0182.3: Jos haluan, voin rajoittaa omaa istumistani KOULUSSA.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

253 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_sePbc_01_T3	Kys0182.3: Jos haluan, voin rajoittaa omaa istumistani KOULUSSA.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	253	912	1165	7	4: 286, NA: 253, 5: 174, 7: 168	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_sePbc_02_T3

Kys0183.3: Voin itse täysin vaikuttaa siihen rajoitanko omaa istumistani KOULUSSA.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

252 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_sePbc_02_T3	Kys0183.3: Voin itse täysin vaikuttaa siihen rajoitanko omaa istumistani KOULUSSA.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	252	913	1165	7	4: 294, NA: 252, 7: 161, 5: 152	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_sePbc_03_T3

Kys0184.3: Jos haluan, voin rajoittaa omaa istumistani VAPAA-AJALLA.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

252 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_sePbc_03_T3	Kys0184.3: Jos haluan, voin rajoittaa omaa istumistani VAPAA-AJALLA.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	252	913	1165	7	7: 390, NA: 252, 4: 191, 6: 134	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_sePbc_04_T3

Kys0185.3: Voin itse täysin vaikuttaa siihen rajoitanko omaa istumistani VAPAA-AJALLA.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

253 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_sePbc_04_T3	Kys0185.3: Voin itse täysin vaikuttaa siihen rajoitanko omaa istumistani VAPAA-AJALLA.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	253	912	1165	7	7: 380, NA: 253, 4: 202, 6: 139	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_sePbc_05_T3

Kys0186.3: Jos haluan, voin rajoittaa omaa istumistani TYÖSSÄ OPPIMASSA.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

259 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_sePbc_05_T3	Kys0186.3: Jos haluan, voin rajoittaa omaa istumistani TYÖSSÄ OPPIMASSA.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	259	906	1165	7	4: 321, NA: 259, 7: 221, 5: 120	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

sitLieAccelerometer_T3

Keskimääräinen makuun ja istumisen (SB) aika päivässä (T3)

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

657 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist	format.spss	display_width
sitLieAccelerometer_T3	Keskimääräinen makuun ja istumisen (SB) aika päivässä (T3)	numeric	657	508	1165	564.11	94.67	317.38	492.63	560.23	627.28	845.63	<U+	2582><	U+2587> F8.2 0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

symptom_neckShoulderPain_T3

Kys0031.3: Niska- tai hartiakipuja

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

235 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
symptom_neckShoulderPain_T3	Kys0031.3: Niska- tai hartiakipuja	labelled	FALSE	Harvoin tai ei lainkaan=1,Noin kerran kuussa=2,Noin kerran viikossa=3,Lähes joka päivä=4	235	930	1165	4	1: 396, 2: 269, NA: 235, 3: 176	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Harvoin tai ei lainkaan: 1
Noin kerran kuussa: 2
Noin kerran viikossa: 3
Lähes joka päivä: 4

symptom_lowerBackPain_T3

Kys0032.3: Selän alaosan kipuja

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

240 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
symptom_lowerBackPain_T3	Kys0032.3: Selän alaosan kipuja	labelled	FALSE	Harvoin tai ei lainkaan=1,Noin kerran kuussa=2,Noin kerran viikossa=3,Lähes joka päivä=4	240	925	1165	4	1: 447, 2: 288, NA: 240, 3: 138	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Harvoin tai ei lainkaan: 1
Noin kerran kuussa: 2
Noin kerran viikossa: 3
Lähes joka päivä: 4

symptom_stomachAche_T3

Kys0033.3: Vatsakipuja

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

249 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
symptom_stomachAche_T3	Kys0033.3: Vatsakipuja	labelled	FALSE	Harvoin tai ei lainkaan=1,Noin kerran kuussa=2,Noin kerran viikossa=3,Lähes joka päivä=4	249	916	1165	4	1: 412, 2: 352, NA: 249, 3: 118	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Harvoin tai ei lainkaan: 1
Noin kerran kuussa: 2
Noin kerran viikossa: 3
Lähes joka päivä: 4

symptom_tensionNervousness_T3

Kys0034.3: Jännittyneisyyttä tai hermostuneisuutta

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

234 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
symptom_tensionNervousness_T3	Kys0034.3: Jännittyneisyyttä tai hermostuneisuutta	labelled	FALSE	Harvoin tai ei lainkaan=1,Noin kerran kuussa=2,Noin kerran viikossa=3,Lähes joka päivä=4	234	931	1165	4	1: 374, 2: 273, NA: 234, 3: 203	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Harvoin tai ei lainkaan: 1
Noin kerran kuussa: 2
Noin kerran viikossa: 3
Lähes joka päivä: 4

symptom_irritabilityAngerbursts_T3

Kys0035.3: Ärtyneisyyttä tai kiukunpurkauksia

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

239 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
symptom_irritabilityAngerbursts_T3	Kys0035.3: Ärtyneisyyttä tai kiukunpurkauksia	labelled	FALSE	Harvoin tai ei lainkaan=1,Noin kerran kuussa=2,Noin kerran viikossa=3,Lähes joka päivä=4	239	926	1165	4	1: 391, 2: 258, NA: 239, 3: 203	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Harvoin tai ei lainkaan: 1
Noin kerran kuussa: 2
Noin kerran viikossa: 3
Lähes joka päivä: 4

symptom_sleepDifficulty_T3

Kys0036.3: Vaikeuksia päästä uneen tai heräilemistä öisin

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

236 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
symptom_sleepDifficulty_T3	Kys0036.3: Vaikeuksia päästä uneen tai heräilemistä öisin	labelled	FALSE	Harvoin tai ei lainkaan=1,Noin kerran kuussa=2,Noin kerran viikossa=3,Lähes joka päivä=4	236	929	1165	4	1: 373, 2: 237, NA: 236, 3: 189	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Harvoin tai ei lainkaan: 1
Noin kerran kuussa: 2
Noin kerran viikossa: 3
Lähes joka päivä: 4

symptom_headAche_T3

Kys0037.3: Päänsärkyä

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

231 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
symptom_headAche_T3	Kys0037.3: Päänsärkyä	labelled	FALSE	Harvoin tai ei lainkaan=1,Noin kerran kuussa=2,Noin kerran viikossa=3,Lähes joka päivä=4	231	934	1165	4	2: 329, 1: 318, NA: 231, 3: 217	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Harvoin tai ei lainkaan: 1
Noin kerran kuussa: 2
Noin kerran viikossa: 3
Lähes joka päivä: 4

symptom_tirednessFaintness_T3

Kys0038.3: Väsymystä tai heikotusta

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

232 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
symptom_tirednessFaintness_T3	Kys0038.3: Väsymystä tai heikotusta	labelled	FALSE	Harvoin tai ei lainkaan=1,Noin kerran kuussa=2,Noin kerran viikossa=3,Lähes joka päivä=4	232	933	1165	4	2: 277, 3: 267, 1: 241, NA: 232	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Harvoin tai ei lainkaan: 1
Noin kerran kuussa: 2
Noin kerran viikossa: 3
Lähes joka päivä: 4

PA_agrbct_T3

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

233 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_agrbct_T3	numeric	233	932	1165	3.21	1.38	1	2.1	3.2	4.1	6

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_amotivation_T3

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

234 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_amotivation_T3	numeric	234	931	1165	1.61	0.84	1	1	1	2	5

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_autonomous_T3

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

233 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_autonomous_T3	numeric	233	932	1165	3.45	1.05	1	2.78	3.44	4.22	5

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_controlled_T3

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

235 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_controlled_T3	numeric	235	930	1165	1.98	0.89	1	1	1.8	2.6	5

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_dnorm_T3

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

233 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_dnorm_T3	numeric	233	932	1165	4.31	1.61	1	3	4	5.5	7

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_frqbct_T3

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

237 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_frqbct_T3	numeric	237	928	1165	2.72	1.24	1	1.67	2.67	3.56	6.11

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_goal_T3

Kys0147.3: Onko sinulla tällä hetkellä liikuntatavoite?

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

257 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_goal_T3	Kys0147.3: Onko sinulla tällä hetkellä liikuntatavoite?	labelled	FALSE	Kyllä (kerro lyhyesti, mikä tämänhetkinen liikuntatavoittees=0,Ei=1	257	908	1165	2	1: 554, 0: 354, NA: 257	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Kyllä (kerro lyhyesti, mikä tämänhetkinen liikuntatavoittees: 0
Ei: 1

PA_inorm_T3

Kys0108.3: Vanhempani haluaisivat minun liikkuvan säännöllisesti, vähintään 1,5 tuntia viik

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

238 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_inorm_T3	Kys0108.3: Vanhempani haluaisivat minun liikkuvan säännöllisesti, vähintään 1,5 tuntia viik	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,3=3,4=4,5=5,6=6,Pitää täysin paikkansa7=7	238	927	1165	7	4: 244, NA: 238, 7: 235, 5: 102	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_intention_T3

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

234 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_intention_T3	numeric	234	931	1165	5.12	1.86	1	4	5.5	7	7

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_outcomeExpectations_T3

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

229 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_outcomeExpectations_T3	numeric	229	936	1165	4.63	0.92	1	4	4.67	5.33	7

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_opportunities_T3

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

229 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_opportunities_T3	numeric	229	936	1165	4.88	1.03	1.43	4	4.86	5.71	7

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_pbc_T3

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

231 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_pbc_T3	numeric	231	934	1165	4.97	1.22	1	4	5	6	7

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_selfefficacy_T3

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

228 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_selfefficacy_T3	numeric	228	937	1165	4.96	1.29	1	4	4.5	6	7

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

SB_dnorm_T3

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

249 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
SB_dnorm_T3	numeric	249	916	1165	3.4	1.56	1	2	4	4	7

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

SB_inorm_T3

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

248 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
SB_inorm_T3	numeric	248	917	1165	4.28	1.35	1	4	4	5	7

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

SB_intention_T3

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

248 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
SB_intention_T3	numeric	248	917	1165	4.01	1.69	1	3	4	5	7

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

SB_outcomeExpectations_T3

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

248 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
SB_outcomeExpectations_T3	numeric	248	917	1165	4.44	1.06	1	4	4.43	5.29	7

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

SB_sePbc_T3

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

249 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
SB_sePbc_T3	numeric	249	916	1165	4.98	1.33	1	4	5	6	7

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

symptom_T3

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

216 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
symptom_T3	numeric	216	949	1165	2	0.7	1	1.5	1.88	2.5	4

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_actionplan_T3

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

235 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_actionplan_T3	numeric	235	930	1165	2.71	0.94	1	2	3	3.25	4

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_copingplan_T3

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

233 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_copingplan_T3	numeric	233	932	1165	2.48	0.92	1	2	2.5	3	4

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_sePbc_T1

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

94 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_sePbc_T1	numeric	94	1071	1165	5.27	1.07	1.75	4.5	5.33	6.08	7

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_sePbc_T3

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

228 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_sePbc_T3	numeric	228	937	1165	4.96	1.08	1	4.17	4.83	5.75	7

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_actCop_T1

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

92 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_actCop_T1	numeric	92	1073	1165	2.63	0.84	1	2	2.75	3.12	4

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_actCop_T3

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

233 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_actCop_T3	numeric	233	932	1165	2.59	0.88	1	2	2.75	3	4

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_extrinsic_01_T1

Kys0080.1: koska muut ihmiset sanovat, että minun pitää liikkua.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

97 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_extrinsic_01_T1	Kys0080.1: koska muut ihmiset sanovat, että minun pitää liikkua.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	97	1068	1165	5	1: 682, 2: 164, 3: 158, NA: 97	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_extrinsic_02_T1

Kys0081.1: koska muut ihmiset ovat tyytymättömiä minuun, jos en liiku.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

96 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_extrinsic_02_T1	Kys0081.1: koska muut ihmiset ovat tyytymättömiä minuun, jos en liiku.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	96	1069	1165	5	1: 784, 2: 129, 3: 109, NA: 96	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_extrinsic_03_T1

Kys0083.1: koska kaverini ja perheeni painostavat minua liikkumaan.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

101 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_extrinsic_03_T1	Kys0083.1: koska kaverini ja perheeni painostavat minua liikkumaan.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	101	1064	1165	5	1: 740, 2: 145, 3: 122, NA: 101	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_introjected_01_T1

Kys0084.1: koska tunnen syyllisyyttä, jos en liiku.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

97 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_introjected_01_T1	Kys0084.1: koska tunnen syyllisyyttä, jos en liiku.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	97	1068	1165	5	1: 518, 3: 219, 2: 134, 4: 108	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_introjected_02_T1

Kys0085.1: koska tunnen itseni epäonnistuneeksi, jos en ole liikkunut vähään aikaan.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

99 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_introjected_02_T1	Kys0085.1: koska tunnen itseni epäonnistuneeksi, jos en ole liikkunut vähään aikaan.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	99	1066	1165	5	1: 457, 3: 212, 2: 161, 4: 135	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_identified_01_T1

Kys0087.1: koska minusta on tärkeää nähdä vaivaa säännöllisen liikunnan eteen.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

102 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_identified_01_T1	Kys0087.1: koska minusta on tärkeää nähdä vaivaa säännöllisen liikunnan eteen.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	102	1063	1165	5	3: 298, 4: 240, 5: 196, 1: 178	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_identified_02_T1

Kys0088.1: koska arvostan liikunnasta saamaani hyötyä.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

102 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_identified_02_T1	Kys0088.1: koska arvostan liikunnasta saamaani hyötyä.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	102	1063	1165	5	5: 391, 4: 275, 3: 225, NA: 102	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_identified_03_T1

Kys0090.1: koska minulle on tärkeää liikkua säännöllisesti.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

95 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_identified_03_T1	Kys0090.1: koska minulle on tärkeää liikkua säännöllisesti.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	95	1070	1165	5	3: 283, 5: 280, 4: 224, 2: 175	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_integrated_01_T1

Kys0089.1: koska se sopii yhteen elämäntavoitteideni kanssa.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

95 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_integrated_01_T1	Kys0089.1: koska se sopii yhteen elämäntavoitteideni kanssa.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	95	1070	1165	5	3: 338, 5: 260, 4: 196, 2: 152	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_integrated_02_T1

Kys0092.1: …koska liikunta sopii yhteen arvojeni kanssa.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

103 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_integrated_02_T1	Kys0092.1: …koska liikunta sopii yhteen arvojeni kanssa.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	103	1062	1165	5	3: 311, 5: 239, 4: 221, 2: 161	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_integrated_03_T1

Kys0094.1: koska liikunta on keskeinen osa sitä, kuka olen.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

99 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_integrated_03_T1	Kys0094.1: koska liikunta on keskeinen osa sitä, kuka olen.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	99	1066	1165	5	3: 256, 5: 224, 4: 206, 2: 201	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_intrinsic_01_T1

Kys0091.1: koska tunnen iloa ja tyytyväisyyttä, kun liikun.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

95 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_intrinsic_01_T1	Kys0091.1: koska tunnen iloa ja tyytyväisyyttä, kun liikun.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	95	1070	1165	5	5: 372, 4: 278, 3: 240, 2: 109	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_intrinsic_02_T1

Kys0093.1: koska liikkuminen on hauskaa.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

99 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_intrinsic_02_T1	Kys0093.1: koska liikkuminen on hauskaa.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	99	1066	1165	5	5: 323, 4: 294, 3: 258, 2: 115	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_intrinsic_03_T1

Kys0095.1: koska nautin liikuntahetkistä.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

108 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_intrinsic_03_T1	Kys0095.1: koska nautin liikuntahetkistä.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	108	1057	1165	5	5: 295, 3: 264, 4: 264, 2: 138	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_intrinsic_T1

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

91 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_intrinsic_T1	numeric	91	1074	1165	3.61	1.14	1	3	3.67	4.67	5

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_integrated_T1

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

92 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_integrated_T1	numeric	92	1073	1165	3.22	1.18	1	2.33	3	4	5

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_identified_T1

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

91 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_identified_T1	numeric	91	1074	1165	3.41	1.1	1	2.67	3.5	4.33	5

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_introjected_T1

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

92 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_introjected_T1	numeric	92	1073	1165	2.24	1.25	1	1	2	3	5

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_extrinsic_T1

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

96 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_extrinsic_T1	numeric	96	1069	1165	1.56	0.83	1	1	1	2	5

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_extrinsic_01_T3

Kys0080.3: koska muut ihmiset sanovat, että minun pitää liikkua.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

237 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_extrinsic_01_T3	Kys0080.3: koska muut ihmiset sanovat, että minun pitää liikkua.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	237	928	1165	5	1: 554, NA: 237, 3: 170, 2: 145	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_extrinsic_02_T3

Kys0081.3: koska muut ihmiset ovat tyytymättömiä minuun, jos en liiku.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

239 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_extrinsic_02_T3	Kys0081.3: koska muut ihmiset ovat tyytymättömiä minuun, jos en liiku.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	239	926	1165	5	1: 611, NA: 239, 2: 146, 3: 115	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_extrinsic_03_T3

Kys0083.3: koska kaverini ja perheeni painostavat minua liikkumaan.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

244 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_extrinsic_03_T3	Kys0083.3: koska kaverini ja perheeni painostavat minua liikkumaan.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	244	921	1165	5	1: 604, NA: 244, 3: 127, 2: 120	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_introjected_01_T3

Kys0084.3: koska tunnen syyllisyyttä, jos en liiku.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

244 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_introjected_01_T3	Kys0084.3: koska tunnen syyllisyyttä, jos en liiku.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	244	921	1165	5	1: 372, NA: 244, 3: 234, 4: 125	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_introjected_02_T3

Kys0085.3: koska tunnen itseni epäonnistuneeksi, jos en ole liikkunut vähään aikaan.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

239 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_introjected_02_T3	Kys0085.3: koska tunnen itseni epäonnistuneeksi, jos en ole liikkunut vähään aikaan.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	239	926	1165	5	1: 335, NA: 239, 3: 217, 2: 140	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_identified_01_T3

Kys0087.3: koska minusta on tärkeää nähdä vaivaa säännöllisen liikunnan eteen.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

241 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_identified_01_T3	Kys0087.3: koska minusta on tärkeää nähdä vaivaa säännöllisen liikunnan eteen.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	241	924	1165	5	3: 279, NA: 241, 4: 193, 5: 178	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_identified_02_T3

Kys0088.3: koska arvostan liikunnasta saamaani hyötyä.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

240 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_identified_02_T3	Kys0088.3: koska arvostan liikunnasta saamaani hyötyä.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	240	925	1165	5	5: 334, NA: 240, 4: 225, 3: 212	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_identified_03_T3

Kys0090.3: koska minulle on tärkeää liikkua säännöllisesti.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

244 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_identified_03_T3	Kys0090.3: koska minulle on tärkeää liikkua säännöllisesti.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	244	921	1165	5	3: 255, NA: 244, 5: 236, 4: 212	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_integrated_01_T3

Kys0089.3: koska se sopii yhteen elämäntavoitteideni kanssa.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

239 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_integrated_01_T3	Kys0089.3: koska se sopii yhteen elämäntavoitteideni kanssa.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	239	926	1165	5	3: 305, NA: 239, 5: 221, 4: 199	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_integrated_02_T3

Kys0092.3: …koska liikunta sopii yhteen arvojeni kanssa.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

239 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_integrated_02_T3	Kys0092.3: …koska liikunta sopii yhteen arvojeni kanssa.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	239	926	1165	5	3: 290, NA: 239, 4: 219, 5: 214	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_integrated_03_T3

Kys0094.3: koska liikunta on keskeinen osa sitä, kuka olen.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

241 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_integrated_03_T3	Kys0094.3: koska liikunta on keskeinen osa sitä, kuka olen.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	241	924	1165	5	3: 268, NA: 241, 5: 204, 4: 165	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_intrinsic_01_T3

Kys0091.3: koska tunnen iloa ja tyytyväisyyttä, kun liikun.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

241 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_intrinsic_01_T3	Kys0091.3: koska tunnen iloa ja tyytyväisyyttä, kun liikun.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	241	924	1165	5	5: 285, 4: 267, NA: 241, 3: 223	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_intrinsic_02_T3

Kys0093.3: koska liikkuminen on hauskaa.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

242 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_intrinsic_02_T3	Kys0093.3: koska liikkuminen on hauskaa.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	242	923	1165	5	5: 279, 4: 273, NA: 242, 3: 235	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_intrinsic_03_T3

Kys0095.3: koska nautin liikuntahetkistä.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

247 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_intrinsic_03_T3	Kys0095.3: koska nautin liikuntahetkistä.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	247	918	1165	5	3: 264, 5: 250, 4: 247, NA: 247	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_intrinsic_T3

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

236 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_intrinsic_T3	numeric	236	929	1165	3.64	1.1	1	3	3.67	4.67	5

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_integrated_T3

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

236 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_integrated_T3	numeric	236	929	1165	3.31	1.16	1	2.67	3.33	4	5

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_identified_T3

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

234 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_identified_T3	numeric	234	931	1165	3.41	1.13	1	2.67	3.33	4.33	5

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_introjected_T3

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

235 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_introjected_T3	numeric	235	930	1165	2.43	1.28	1	1	2.5	3.5	5

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_extrinsic_T3

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

237 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_extrinsic_T3	numeric	237	928	1165	1.67	0.91	1	1	1	2.33	5

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_actplan_01_diff

Kys0115.3: … milloin liikkua

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

309 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_actplan_01_diff	Kys0115.3: … milloin liikkua	labelled	FALSE	Ei pidä paikkaansa1=1,Ei pidä enimmäkseen paikkaansa2=2,Pitää enimmäkseen paikkansa3=3,Pitää täysin paikkansa4=4	309	856	1165	7	0: 405, NA: 309, -1: 169, 1: 156	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä paikkaansa1: 1
Ei pidä enimmäkseen paikkaansa2: 2
Pitää enimmäkseen paikkansa3: 3
Pitää täysin paikkansa4: 4

PA_actplan_02_diff

Kys0116.3: … missä liikkua

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

311 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_actplan_02_diff	Kys0116.3: … missä liikkua	labelled	FALSE	Ei pidä paikkaansa1=1,Ei pidä enimmäkseen paikkaansa2=2,Pitää enimmäkseen paikkansa3=3,Pitää täysin paikkansa4=4	311	854	1165	7	0: 436, NA: 311, -1: 153, 1: 135	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä paikkaansa1: 1
Ei pidä enimmäkseen paikkaansa2: 2
Pitää enimmäkseen paikkansa3: 3
Pitää täysin paikkansa4: 4

PA_actplan_03_diff

Kys0117.3: … kuinka liikkua

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

313 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_actplan_03_diff	Kys0117.3: … kuinka liikkua	labelled	FALSE	Ei pidä paikkaansa1=1,Ei pidä enimmäkseen paikkaansa2=2,Pitää enimmäkseen paikkansa3=3,Pitää täysin paikkansa4=4	313	852	1165	7	0: 434, NA: 313, -1: 164, 1: 123	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä paikkaansa1: 1
Ei pidä enimmäkseen paikkaansa2: 2
Pitää enimmäkseen paikkansa3: 3
Pitää täysin paikkansa4: 4

PA_actplan_04_diff

Kys0118.3: … kuinka usein liikkua

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

310 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_actplan_04_diff	Kys0118.3: … kuinka usein liikkua	labelled	FALSE	Ei pidä paikkaansa1=1,Ei pidä enimmäkseen paikkaansa2=2,Pitää enimmäkseen paikkansa3=3,Pitää täysin paikkansa4=4	310	855	1165	7	0: 435, NA: 310, -1: 170, 1: 136	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä paikkaansa1: 1
Ei pidä enimmäkseen paikkaansa2: 2
Pitää enimmäkseen paikkansa3: 3
Pitää täysin paikkansa4: 4

PA_agrbct_01_diff

Kys0128.3: Olen asettanut itselleni liikuntatavoitteita.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

304 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_agrbct_01_diff	Kys0128.3: Olen asettanut itselleni liikuntatavoitteita.	labelled	FALSE	Ei pidä lainkaan paikkaansa0=1,1=2,2=3,3=4,4=5,Pitää täysin paikkansa5=6	304	861	1165	11	0: 322, NA: 304, 1: 112, -1: 110	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa0: 1
1: 2
2: 3
3: 4
4: 5
Pitää täysin paikkansa5: 6

PA_agrbct_02_diff

Kys0129.3: Olen itse tehnyt tarkan suunnitelman (mitä, missä, milloin) omaehtoisen liikun

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

306 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_agrbct_02_diff	Kys0129.3: Olen itse tehnyt tarkan suunnitelman (mitä, missä, milloin) omaehtoisen liikun	labelled	FALSE	Ei pidä lainkaan paikkaansa0=1,1=2,2=3,3=4,4=5,Pitää täysin paikkansa5=6	306	859	1165	11	0: 315, NA: 306, 1: 126, -1: 122	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa0: 1
1: 2
2: 3
3: 4
4: 5
Pitää täysin paikkansa5: 6

PA_agrbct_03_diff

Kys0130.3: Minulla on liikuntasuunnitelma, jonka joku muu, esim. liikuntaseurani, on tehnyt

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

306 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_agrbct_03_diff	Kys0130.3: Minulla on liikuntasuunnitelma, jonka joku muu, esim. liikuntaseurani, on tehnyt	labelled	FALSE	Ei pidä lainkaan paikkaansa0=1,1=2,2=3,3=4,4=5,Pitää täysin paikkansa5=6	306	859	1165	11	0: 425, NA: 306, 1: 94, -1: 68	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa0: 1
1: 2
2: 3
3: 4
4: 5
Pitää täysin paikkansa5: 6

PA_agrbct_04_diff

Kys0131.3: Minulla on tapa, jolla muistutan itseäni liikuntasuunnitelmastani, esim. kirjoit

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

304 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_agrbct_04_diff	Kys0131.3: Minulla on tapa, jolla muistutan itseäni liikuntasuunnitelmastani, esim. kirjoit	labelled	FALSE	Ei pidä lainkaan paikkaansa0=1,1=2,2=3,3=4,4=5,Pitää täysin paikkansa5=6	304	861	1165	11	0: 348, NA: 304, 1: 117, -1: 89	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa0: 1
1: 2
2: 3
3: 4
4: 5
Pitää täysin paikkansa5: 6

PA_agrbct_05_diff

Kys0132.3: Olen pilkkonut laajempia liikuntatavoitteitani pienempiin osatavoitteisiin.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

305 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_agrbct_05_diff	Kys0132.3: Olen pilkkonut laajempia liikuntatavoitteitani pienempiin osatavoitteisiin.	labelled	FALSE	Ei pidä lainkaan paikkaansa0=1,1=2,2=3,3=4,4=5,Pitää täysin paikkansa5=6	305	860	1165	11	0: 339, NA: 305, 1: 137, -1: 101	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa0: 1
1: 2
2: 3
3: 4
4: 5
Pitää täysin paikkansa5: 6

PA_agrbct_06_diff

Kys0133.3: Olen kokeillut minulle uusia tapoja liikkua.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

314 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_agrbct_06_diff	Kys0133.3: Olen kokeillut minulle uusia tapoja liikkua.	labelled	FALSE	Ei pidä lainkaan paikkaansa0=1,1=2,2=3,3=4,4=5,Pitää täysin paikkansa5=6	314	851	1165	11	0: 315, NA: 314, 1: 133, -1: 114	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa0: 1
1: 2
2: 3
3: 4
4: 5
Pitää täysin paikkansa5: 6

PA_agrbct_07_diff

Kys0134.3: Olen pohtinut, millaiset vaikeat tilanteet tai esteet estävät minua toteuttamast

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

312 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_agrbct_07_diff	Kys0134.3: Olen pohtinut, millaiset vaikeat tilanteet tai esteet estävät minua toteuttamast	labelled	FALSE	Ei pidä lainkaan paikkaansa0=1,1=2,2=3,3=4,4=5,Pitää täysin paikkansa5=6	312	853	1165	11	NA: 312, 0: 281, 1: 130, -1: 104	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa0: 1
1: 2
2: 3
3: 4
4: 5
Pitää täysin paikkansa5: 6

PA_agrbct_08_diff

Kys0135.3: Olen suunnitellut tapoja ylittää liikunnan harrastamisen esteitä.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

307 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_agrbct_08_diff	Kys0135.3: Olen suunnitellut tapoja ylittää liikunnan harrastamisen esteitä.	labelled	FALSE	Ei pidä lainkaan paikkaansa0=1,1=2,2=3,3=4,4=5,Pitää täysin paikkansa5=6	307	858	1165	11	NA: 307, 0: 289, 1: 139, -1: 123	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa0: 1
1: 2
2: 3
3: 4
4: 5
Pitää täysin paikkansa5: 6

PA_agrbct_09_diff

Kys0136.3: Olen miettinyt, miten liikunta sopii omaan minäkuvaani.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

307 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_agrbct_09_diff	Kys0136.3: Olen miettinyt, miten liikunta sopii omaan minäkuvaani.	labelled	FALSE	Ei pidä lainkaan paikkaansa0=1,1=2,2=3,3=4,4=5,Pitää täysin paikkansa5=6	307	858	1165	11	NA: 307, 0: 299, 1: 149, -1: 132	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa0: 1
1: 2
2: 3
3: 4
4: 5
Pitää täysin paikkansa5: 6

PA_agrbct_10_diff

Kys0137.3: Olen pyrkinyt löytämään tapoja liikkua siten, että se ei häiritse vaan tukee mui

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

310 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_agrbct_10_diff	Kys0137.3: Olen pyrkinyt löytämään tapoja liikkua siten, että se ei häiritse vaan tukee mui	labelled	FALSE	Ei pidä lainkaan paikkaansa0=1,1=2,2=3,3=4,4=5,Pitää täysin paikkansa5=6	310	855	1165	11	NA: 310, 0: 296, 1: 137, -1: 129	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa0: 1
1: 2
2: 3
3: 4
4: 5
Pitää täysin paikkansa5: 6

PA_amotivation_01_diff

Kys0082.3: En ymmärrä, miksi minun pitäisi liikkua vapaa-ajallani.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

317 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_amotivation_01_diff	Kys0082.3: En ymmärrä, miksi minun pitäisi liikkua vapaa-ajallani.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	317	848	1165	9	0: 564, NA: 317, 1: 75, -1: 72	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_amotivation_02_diff

Kys0086.3: En näe mitään syytä liikkua vapaa-ajallani.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

318 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_amotivation_02_diff	Kys0086.3: En näe mitään syytä liikkua vapaa-ajallani.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	318	847	1165	9	0: 569, NA: 318, 1: 82, -1: 75	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_amotivation_03_diff

Kys0096.3: En näe, mitä järkeä on liikkua vapaa-ajalla.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

312 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_amotivation_03_diff	Kys0096.3: En näe, mitä järkeä on liikkua vapaa-ajalla.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	312	853	1165	9	0: 520, NA: 312, 1: 96, -1: 80	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_amotivation_04_diff

Kys0097.3: Mielestäni liikkuminen on ajanhukkaa.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

308 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_amotivation_04_diff	Kys0097.3: Mielestäni liikkuminen on ajanhukkaa.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	308	857	1165	9	0: 578, NA: 308, 1: 82, -1: 65	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_copplan_01_diff

Kys0119.3: … mitä tehdä silloin, kun jokin sotkee suunnitelmani

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

301 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_copplan_01_diff	Kys0119.3: … mitä tehdä silloin, kun jokin sotkee suunnitelmani	labelled	FALSE	Ei pidä paikkaansa1=1,Ei pidä enimmäkseen paikkaansa2=2,Pitää enimmäkseen paikkansa3=3,Pitää täysin paikkansa4=4	301	864	1165	7	0: 384, NA: 301, -1: 190, 1: 176	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä paikkaansa1: 1
Ei pidä enimmäkseen paikkaansa2: 2
Pitää enimmäkseen paikkansa3: 3
Pitää täysin paikkansa4: 4

PA_copplan_02_diff

Kys0120.3: … kuinka selviytyä repsahduksista

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

303 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_copplan_02_diff	Kys0120.3: … kuinka selviytyä repsahduksista	labelled	FALSE	Ei pidä paikkaansa1=1,Ei pidä enimmäkseen paikkaansa2=2,Pitää enimmäkseen paikkansa3=3,Pitää täysin paikkansa4=4	303	862	1165	7	0: 398, NA: 303, 1: 171, -1: 157	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä paikkaansa1: 1
Ei pidä enimmäkseen paikkaansa2: 2
Pitää enimmäkseen paikkansa3: 3
Pitää täysin paikkansa4: 4

PA_copplan_03_diff

Kys0121.3: … kuinka pysyä suunnitelmissa vaikeissakin tilanteissa

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

304 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_copplan_03_diff	Kys0121.3: … kuinka pysyä suunnitelmissa vaikeissakin tilanteissa	labelled	FALSE	Ei pidä paikkaansa1=1,Ei pidä enimmäkseen paikkaansa2=2,Pitää enimmäkseen paikkansa3=3,Pitää täysin paikkansa4=4	304	861	1165	7	0: 415, NA: 304, -1: 173, 1: 154	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä paikkaansa1: 1
Ei pidä enimmäkseen paikkaansa2: 2
Pitää enimmäkseen paikkansa3: 3
Pitää täysin paikkansa4: 4

PA_copplan_04_diff

Kys0122.3: … kuinka hyödyntää hyviä tilaisuuksia liikkumiseen

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

307 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_copplan_04_diff	Kys0122.3: … kuinka hyödyntää hyviä tilaisuuksia liikkumiseen	labelled	FALSE	Ei pidä paikkaansa1=1,Ei pidä enimmäkseen paikkaansa2=2,Pitää enimmäkseen paikkansa3=3,Pitää täysin paikkansa4=4	307	858	1165	7	0: 411, NA: 307, -1: 191, 1: 156	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä paikkaansa1: 1
Ei pidä enimmäkseen paikkaansa2: 2
Pitää enimmäkseen paikkansa3: 3
Pitää täysin paikkansa4: 4

PA_dnorm_02_diff

Kys0107.3: Vanhempani liikkuvat säännöllisesti, vähintään 1,5 tuntia viikoittain

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

303 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_dnorm_02_diff	Kys0107.3: Vanhempani liikkuvat säännöllisesti, vähintään 1,5 tuntia viikoittain	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,3=3,4=4,5=5,6=6,Pitää täysin paikkansa7=7	303	862	1165	13	0: 324, NA: 303, -1: 135, 1: 121	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_dnorm_01_diff

Kys0106.3: Suurin osa ystävistäni liikkuu säännöllisesti, vähintään 1,5 tuntia viikoittain

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

301 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_dnorm_01_diff	Kys0106.3: Suurin osa ystävistäni liikkuu säännöllisesti, vähintään 1,5 tuntia viikoittain	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,3=3,4=4,5=5,6=6,Pitää täysin paikkansa7=7	301	864	1165	13	0: 312, NA: 301, -1: 133, 1: 124	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_controlled_01_diff

Kys0080.3: koska muut ihmiset sanovat, että minun pitää liikkua.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

306 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_controlled_01_diff	Kys0080.3: koska muut ihmiset sanovat, että minun pitää liikkua.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	306	859	1165	9	0: 513, NA: 306, 1: 106, -1: 101	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_controlled_02_diff

Kys0081.3: koska muut ihmiset ovat tyytymättömiä minuun, jos en liiku.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

306 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_controlled_02_diff	Kys0081.3: koska muut ihmiset ovat tyytymättömiä minuun, jos en liiku.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	306	859	1165	9	0: 575, NA: 306, 1: 106, -1: 63	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_controlled_03_diff

Kys0083.3: koska kaverini ja perheeni painostavat minua liikkumaan.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

313 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_controlled_03_diff	Kys0083.3: koska kaverini ja perheeni painostavat minua liikkumaan.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	313	852	1165	9	0: 538, NA: 313, 1: 104, -1: 92	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_frqbct_01_diff

Kys0138.3: Olen muistuttanut mieleeni myös vapaa-ajallani, millaisia myönteisiä seurauksia

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

305 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_frqbct_01_diff	Kys0138.3: Olen muistuttanut mieleeni myös vapaa-ajallani, millaisia myönteisiä seurauksia	labelled	FALSE	En kertaakaan0=1,Kerran1=2,Kahdesti2=3,Viikoittain3=4,Noin joka toinen päivä4=5,Päivittäin5=6	305	860	1165	11	NA: 305, 0: 299, -1: 160, 1: 137	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

En kertaakaan0: 1
Kerran1: 2
Kahdesti2: 3
Viikoittain3: 4
Noin joka toinen päivä4: 5
Päivittäin5: 6

PA_frqbct_02_diff

Kys0139.3: Olen seurannut liikkumistani merkitsemällä liikuntakerrat paperiseen liikkumispä

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

309 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_frqbct_02_diff	Kys0139.3: Olen seurannut liikkumistani merkitsemällä liikuntakerrat paperiseen liikkumispä	labelled	FALSE	En kertaakaan0=1,Kerran1=2,Kahdesti2=3,Viikoittain3=4,Noin joka toinen päivä4=5,Päivittäin5=6	309	856	1165	11	0: 444, NA: 309, 1: 104, 2: 71	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

En kertaakaan0: 1
Kerran1: 2
Kahdesti2: 3
Viikoittain3: 4
Noin joka toinen päivä4: 5
Päivittäin5: 6

PA_frqbct_03_diff

Kys0140.3: Olen seurannut liikkumistani käyttämällä älypuhelinta, esim. Moves-appia.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

309 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_frqbct_03_diff	Kys0140.3: Olen seurannut liikkumistani käyttämällä älypuhelinta, esim. Moves-appia.	labelled	FALSE	En kertaakaan0=1,Kerran1=2,Kahdesti2=3,Viikoittain3=4,Noin joka toinen päivä4=5,Päivittäin5=6	309	856	1165	11	0: 468, NA: 309, 1: 80, 2: 71	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

En kertaakaan0: 1
Kerran1: 2
Kahdesti2: 3
Viikoittain3: 4
Noin joka toinen päivä4: 5
Päivittäin5: 6

PA_frqbct_04_diff

Kys0141.3: Käytän muistivihjeitä, joiden avulla muistan toteuttaa liikunta-aikomukseni.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

311 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_frqbct_04_diff	Kys0141.3: Käytän muistivihjeitä, joiden avulla muistan toteuttaa liikunta-aikomukseni.	labelled	FALSE	En kertaakaan0=1,Kerran1=2,Kahdesti2=3,Viikoittain3=4,Noin joka toinen päivä4=5,Päivittäin5=6	311	854	1165	11	0: 460, NA: 311, 1: 80, 2: 73	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

En kertaakaan0: 1
Kerran1: 2
Kahdesti2: 3
Viikoittain3: 4
Noin joka toinen päivä4: 5
Päivittäin5: 6

PA_frqbct_05_diff

Kys0142.3: Olen verrannut toteutunutta liikuntaani asettamaani liikuntatavoitteeseen.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

314 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_frqbct_05_diff	Kys0142.3: Olen verrannut toteutunutta liikuntaani asettamaani liikuntatavoitteeseen.	labelled	FALSE	En kertaakaan0=1,Kerran1=2,Kahdesti2=3,Viikoittain3=4,Noin joka toinen päivä4=5,Päivittäin5=6	314	851	1165	11	0: 345, NA: 314, 1: 116, 2: 88	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

En kertaakaan0: 1
Kerran1: 2
Kahdesti2: 3
Viikoittain3: 4
Noin joka toinen päivä4: 5
Päivittäin5: 6

PA_frqbct_06_diff

Kys0143.3: Olen miettinyt, mitkä liikunnan harrastamisen syyt ovat minulle itselleni tärkei

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

313 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_frqbct_06_diff	Kys0143.3: Olen miettinyt, mitkä liikunnan harrastamisen syyt ovat minulle itselleni tärkei	labelled	FALSE	En kertaakaan0=1,Kerran1=2,Kahdesti2=3,Viikoittain3=4,Noin joka toinen päivä4=5,Päivittäin5=6	313	852	1165	11	NA: 313, 0: 299, 1: 138, -1: 122	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

En kertaakaan0: 1
Kerran1: 2
Kahdesti2: 3
Viikoittain3: 4
Noin joka toinen päivä4: 5
Päivittäin5: 6

PA_frqbct_07_diff

Kys0144.3: Olen tehnyt muutoksia kotiini (esim. huoneeseeni tai tietokoneelleni), jotta lii

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

310 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_frqbct_07_diff	Kys0144.3: Olen tehnyt muutoksia kotiini (esim. huoneeseeni tai tietokoneelleni), jotta lii	labelled	FALSE	En kertaakaan0=1,Kerran1=2,Kahdesti2=3,Viikoittain3=4,Noin joka toinen päivä4=5,Päivittäin5=6	310	855	1165	11	0: 410, NA: 310, 1: 97, -1: 88	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

En kertaakaan0: 1
Kerran1: 2
Kahdesti2: 3
Viikoittain3: 4
Noin joka toinen päivä4: 5
Päivittäin5: 6

PA_frqbct_08_diff

Kys0145.3: Olen pyytänyt kavereiltani tai perheeltäni tukea liikuntatavoitteideni saavuttam

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

309 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_frqbct_08_diff	Kys0145.3: Olen pyytänyt kavereiltani tai perheeltäni tukea liikuntatavoitteideni saavuttam	labelled	FALSE	En kertaakaan0=1,Kerran1=2,Kahdesti2=3,Viikoittain3=4,Noin joka toinen päivä4=5,Päivittäin5=6	309	856	1165	11	0: 351, NA: 309, 1: 110, -1: 105	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

En kertaakaan0: 1
Kerran1: 2
Kahdesti2: 3
Viikoittain3: 4
Noin joka toinen päivä4: 5
Päivittäin5: 6

PA_frqbct_09_diff

Kys0146.3: Jos en ole saavuttanut liikuntatavoitettani, olen arvioinut, mikä meni pieleen.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

317 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_frqbct_09_diff	Kys0146.3: Jos en ole saavuttanut liikuntatavoitettani, olen arvioinut, mikä meni pieleen.	labelled	FALSE	En kertaakaan0=1,Kerran1=2,Kahdesti2=3,Viikoittain3=4,Noin joka toinen päivä4=5,Päivittäin5=6,Saavutin tavoitteeni6=7	317	848	1165	13	0: 319, NA: 317, 1: 125, -1: 95	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

En kertaakaan0: 1
Kerran1: 2
Kahdesti2: 3
Viikoittain3: 4
Noin joka toinen päivä4: 5
Päivittäin5: 6
Saavutin tavoitteeni6: 7

PA_goal_01_diff

Kys0147.3: Onko sinulla tällä hetkellä liikuntatavoite?

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

330 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_goal_01_diff	Kys0147.3: Onko sinulla tällä hetkellä liikuntatavoite?	labelled	FALSE	Kyllä (kerro lyhyesti, mikä tämänhetkinen liikuntatavoittees=0,Ei=1	330	835	1165	3	0: 600, NA: 330, 1: 143, -1: 92	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Kyllä (kerro lyhyesti, mikä tämänhetkinen liikuntatavoittees: 0
Ei: 1

PA_autonomous_01_diff

Kys0087.3: koska minusta on tärkeää nähdä vaivaa säännöllisen liikunnan eteen.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

314 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_autonomous_01_diff	Kys0087.3: koska minusta on tärkeää nähdä vaivaa säännöllisen liikunnan eteen.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	314	851	1165	9	0: 348, NA: 314, -1: 154, 1: 152	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_autonomous_02_diff

Kys0088.3: koska arvostan liikunnasta saamaani hyötyä.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

312 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_autonomous_02_diff	Kys0088.3: koska arvostan liikunnasta saamaani hyötyä.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	312	853	1165	9	0: 413, NA: 312, 1: 134, -1: 132	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_autonomous_03_diff

Kys0090.3: koska minulle on tärkeää liikkua säännöllisesti.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

310 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_autonomous_03_diff	Kys0090.3: koska minulle on tärkeää liikkua säännöllisesti.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	310	855	1165	9	0: 389, NA: 310, 1: 176, -1: 156	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_inorm_01_diff

Kys0108.3: Vanhempani haluaisivat minun liikkuvan säännöllisesti, vähintään 1,5 tuntia viik

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

304 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_inorm_01_diff	Kys0108.3: Vanhempani haluaisivat minun liikkuvan säännöllisesti, vähintään 1,5 tuntia viik	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,3=3,4=4,5=5,6=6,Pitää täysin paikkansa7=7	304	861	1165	13	0: 321, NA: 304, 1: 121, -1: 111	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_autonomous_04_diff

Kys0089.3: koska se sopii yhteen elämäntavoitteideni kanssa.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

306 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_autonomous_04_diff	Kys0089.3: koska se sopii yhteen elämäntavoitteideni kanssa.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	306	859	1165	9	0: 398, NA: 306, 1: 188, -1: 142	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_autonomous_05_diff

Kys0092.3: …koska liikunta sopii yhteen arvojeni kanssa.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

312 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_autonomous_05_diff	Kys0092.3: …koska liikunta sopii yhteen arvojeni kanssa.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	312	853	1165	9	0: 410, NA: 312, 1: 183, -1: 128	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_autonomous_06_diff

Kys0094.3: koska liikunta on keskeinen osa sitä, kuka olen.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

310 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_autonomous_06_diff	Kys0094.3: koska liikunta on keskeinen osa sitä, kuka olen.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	310	855	1165	9	0: 415, NA: 310, 1: 182, -1: 126	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_intention_01_diff

Kys0113.3: Aion liikkua säännöllisesti viikoittain vähintään 1,5 tuntia seuraavan kuukauden

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

311 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_intention_01_diff	Kys0113.3: Aion liikkua säännöllisesti viikoittain vähintään 1,5 tuntia seuraavan kuukauden	labelled	FALSE	Epätodennäköistä1=1,2=2,3=3,4=4,5=5,6=6,Todennäköistä7=7	311	854	1165	13	0: 375, NA: 311, -1: 111, 1: 93	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Epätodennäköistä1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Todennäköistä7: 7

PA_intention_02_diff

Kys0114.3: Aion liikkua säännöllisesti viikoittain vähintään 1,5 tuntia seuraavan kuukauden

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

307 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_intention_02_diff	Kys0114.3: Aion liikkua säännöllisesti viikoittain vähintään 1,5 tuntia seuraavan kuukauden	labelled	FALSE	Ehdottomasti en1=1,2=2,3=3,4=4,5=5,6=6,Ehdottomasti kyllä7=7	307	858	1165	13	0: 384, NA: 307, -1: 103, 1: 97	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ehdottomasti en1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Ehdottomasti kyllä7: 7

PA_autonomous_07_diff

Kys0091.3: koska tunnen iloa ja tyytyväisyyttä, kun liikun.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

306 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_autonomous_07_diff	Kys0091.3: koska tunnen iloa ja tyytyväisyyttä, kun liikun.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	306	859	1165	9	0: 449, NA: 306, -1: 152, 1: 139	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_autonomous_08_diff

Kys0093.3: koska liikkuminen on hauskaa.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

314 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_autonomous_08_diff	Kys0093.3: koska liikkuminen on hauskaa.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	314	851	1165	9	0: 435, NA: 314, 1: 160, -1: 148	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_autonomous_09_diff

Kys0095.3: koska nautin liikuntahetkistä.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

321 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_autonomous_09_diff	Kys0095.3: koska nautin liikuntahetkistä.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	321	844	1165	9	0: 408, NA: 321, 1: 171, -1: 148	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_controlled_04_diff

Kys0084.3: koska tunnen syyllisyyttä, jos en liiku.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

309 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_controlled_04_diff	Kys0084.3: koska tunnen syyllisyyttä, jos en liiku.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	309	856	1165	9	0: 430, NA: 309, 1: 125, -1: 100	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_controlled_05_diff

Kys0085.3: koska tunnen itseni epäonnistuneeksi, jos en ole liikkunut vähään aikaan.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

309 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_controlled_05_diff	Kys0085.3: koska tunnen itseni epäonnistuneeksi, jos en ole liikkunut vähään aikaan.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	309	856	1165	9	0: 396, NA: 309, 1: 156, -1: 109	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_outcomeExpectations_01_diff

Kys0068.3: Se saisi minut hyvälle tuulelle

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

304 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_outcomeExpectations_01_diff	Kys0068.3: Se saisi minut hyvälle tuulelle	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	304	861	1165	13	0: 377, NA: 304, -1: 134, 1: 123	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_outcomeExpectations_03_diff

Kys0070.3: Se auttaisi pitämään painoni kurissa

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

314 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_outcomeExpectations_03_diff	Kys0070.3: Se auttaisi pitämään painoni kurissa	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	314	851	1165	13	0: 356, NA: 314, 1: 129, -1: 116	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_outcomeExpectations_04_diff

Kys0071.3: Se auttaisi kasvattamaan lihasmassaa

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

305 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_outcomeExpectations_04_diff	Kys0071.3: Se auttaisi kasvattamaan lihasmassaa	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	305	860	1165	13	0: 350, NA: 305, 1: 146, -1: 117	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_outcomeExpectations_05_diff

Kys0072.3: Se parantaisi kykyäni tehdä töitä ja päivittäisiä askareitani

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

307 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_outcomeExpectations_05_diff	Kys0072.3: Se parantaisi kykyäni tehdä töitä ja päivittäisiä askareitani	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	307	858	1165	13	0: 311, NA: 307, -1: 154, 1: 140	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_outcomeExpectations_06_diff

Kys0073.3: Se auttaisi minua jaksamaan

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

307 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_outcomeExpectations_06_diff	Kys0073.3: Se auttaisi minua jaksamaan	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	307	858	1165	13	0: 323, NA: 307, -1: 165, 1: 156	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_outcomeExpectations_07_diff

Kys0074.3: Saisin sen avulla uusia kokemuksia

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

313 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_outcomeExpectations_07_diff	Kys0074.3: Saisin sen avulla uusia kokemuksia	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	313	852	1165	13	0: 314, NA: 313, 1: 151, -1: 140	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_outcomeExpectations_10_diff

Kys0077.3: Se auttaisi minua nukkumaan paremmin

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

307 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_outcomeExpectations_10_diff	Kys0077.3: Se auttaisi minua nukkumaan paremmin	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	307	858	1165	13	0: 350, NA: 307, -1: 156, 1: 140	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_outcomeExpectations_11_diff

Kys0078.3: Saisin sen avulla onnistumisen kokemuksia

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

313 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_outcomeExpectations_11_diff	Kys0078.3: Saisin sen avulla onnistumisen kokemuksia	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	313	852	1165	13	0: 334, NA: 313, 1: 145, -1: 141	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_outcomeExpectations_12_diff

Kys0079.3: Se tukisi itsetuntoani

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

311 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_outcomeExpectations_12_diff	Kys0079.3: Se tukisi itsetuntoani	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	311	854	1165	13	0: 345, NA: 311, -1: 128, 1: 122	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_outcomeExpectationsNegative_02_diff

Kys0069.3: Se veisi liikaa aikaa muilta elämäni tärkeiltä asioilta

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

311 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_outcomeExpectationsNegative_02_diff	Kys0069.3: Se veisi liikaa aikaa muilta elämäni tärkeiltä asioilta	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	311	854	1165	13	0: 329, NA: 311, 1: 149, -1: 102	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_outcomeExpectationsNegative_08_diff

Kys0075.3: Se olisi stressaavaa ja henkisesti rasittavaa

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

309 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_outcomeExpectationsNegative_08_diff	Kys0075.3: Se olisi stressaavaa ja henkisesti rasittavaa	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	309	856	1165	13	0: 343, NA: 309, 1: 147, -1: 129	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_outcomeExpectationsNegative_09_diff

Kys0076.3: Se olisi ikävällä tavalla fyysisesti väsyttävää

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

314 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_outcomeExpectationsNegative_09_diff	Kys0076.3: Se olisi ikävällä tavalla fyysisesti väsyttävää	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	314	851	1165	13	0: 337, NA: 314, 1: 149, -1: 103	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_opportunities_01_diff

Kys0098.3: Minulla on riittävästi rahaa liikunnan harrastamiseen

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

306 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_opportunities_01_diff	Kys0098.3: Minulla on riittävästi rahaa liikunnan harrastamiseen	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Pitää täysin paikkansa7=7	306	859	1165	13	0: 355, NA: 306, -1: 109, 1: 109	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_opportunities_02_diff

Kys0099.3: Ympäristössäni on hyviä pyöräteitä ja lenkkipolkuja

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

306 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_opportunities_02_diff	Kys0099.3: Ympäristössäni on hyviä pyöräteitä ja lenkkipolkuja	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Pitää täysin paikkansa7=7	306	859	1165	13	0: 344, NA: 306, -1: 139, 1: 132	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_opportunities_04_diff

Kys0101.3: Lähistölläni on paljon hyviä liikuntapaikkoja (esim. urheiluhalleja, kuntosaleja

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

302 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_opportunities_04_diff	Kys0101.3: Lähistölläni on paljon hyviä liikuntapaikkoja (esim. urheiluhalleja, kuntosaleja	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Pitää täysin paikkansa7=7	302	863	1165	13	0: 379, NA: 302, -1: 118, 1: 109	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_opportunities_05_diff

Kys0102.3: Liikuntavälineiden puute ei ole este liikkumiselleni

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

309 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_opportunities_05_diff	Kys0102.3: Liikuntavälineiden puute ei ole este liikkumiselleni	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Pitää täysin paikkansa7=7	309	856	1165	13	0: 348, NA: 309, -1: 106, 1: 91	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_opportunities_07_diff

Kys0104.3: Minulla on paljon mahdollisuuksia harrastaa liikuntaa kotona

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

303 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_opportunities_07_diff	Kys0104.3: Minulla on paljon mahdollisuuksia harrastaa liikuntaa kotona	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Pitää täysin paikkansa7=7	303	862	1165	13	NA: 303, 0: 292, 1: 148, -1: 111	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_opportunitiesReverseCoded_03_diff

Kys0100.3: Minulla ei ole tarvitsemiani liikuntavälineitä

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

309 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_opportunitiesReverseCoded_03_diff	Kys0100.3: Minulla ei ole tarvitsemiani liikuntavälineitä	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Pitää täysin paikkansa7=7	309	856	1165	13	0: 323, NA: 309, 1: 106, -1: 97	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_opportunitiesReverseCoded_06_diff

Kys0103.3: Minulla on paljon kiireitä koulun, harrastusten ja/tai kaverien vuoksi

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

312 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_opportunitiesReverseCoded_06_diff	Kys0103.3: Minulla on paljon kiireitä koulun, harrastusten ja/tai kaverien vuoksi	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,3=3,Ei eri eikä samaa mieltä4=4,5=5,6=6,Pitää täysin paikkansa7=7	312	853	1165	13	NA: 312, 0: 262, -1: 140, 1: 122	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
3: 3
Ei eri eikä samaa mieltä4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_pbc_01_diff

Kys0125.3: Voin itse täysin vaikuttaa siihen, liikunko säännöllisesti.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

300 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_pbc_01_diff	Kys0125.3: Voin itse täysin vaikuttaa siihen, liikunko säännöllisesti.	labelled	FALSE	Ei pidä lainkaan paikkaansa1=1,2=2,3=3,4=4,5=5,6=6,Pitää täysin paikkansa7=7	300	865	1165	12	0: 382, NA: 300, -1: 136, 1: 95	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_pbc_03_diff

Kys0127.3: Olen varma, että pystyisin voittamaan hankaluudet, jotka estävät minua liikkumas

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

304 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_pbc_03_diff	Kys0127.3: Olen varma, että pystyisin voittamaan hankaluudet, jotka estävät minua liikkumas	labelled	FALSE	Ei pidä lainkaan paikkaansa1=1,2=2,3=3,4=4,5=5,6=6,Pitää täysin paikkansa7=7	304	861	1165	13	0: 309, NA: 304, -1: 144, 1: 100	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_pbcReverseCoded_02_diff

Kys0126.3: Liikkuminen säännöllisesti ei riipu täysin minusta.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

306 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_pbcReverseCoded_02_diff	Kys0126.3: Liikkuminen säännöllisesti ei riipu täysin minusta.	labelled	FALSE	Ei pidä lainkaan paikkaansa1=1,2=2,3=3,4=4,5=5,6=6,Pitää täysin paikkansa7=7	306	859	1165	13	NA: 306, 0: 281, -1: 128, 1: 86	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkaansa1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_selfefficacy_01_diff

Kys0123.3: Jos haluaisin, voisin liikkua säännöllisesti.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

302 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_selfefficacy_01_diff	Kys0123.3: Jos haluaisin, voisin liikkua säännöllisesti.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,4=4,5=5,6=6,Täysin samaa mieltä7=7	302	863	1165	13	0: 402, NA: 302, -1: 101, 1: 95	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

PA_selfefficacyReverseCoded_02_diff

Kys0124.3: Liikkuminen säännöllisesti on minulle

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

298 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_selfefficacyReverseCoded_02_diff	Kys0124.3: Liikkuminen säännöllisesti on minulle	labelled	FALSE	Helppoa1=1,2=2,3=3,4=4,5=5,6=6,Vaikeaa7=7	298	867	1165	13	NA: 298, 0: 260, -1: 147, 1: 105	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Helppoa1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Vaikeaa7: 7

paAccelerometer_diff

Keskimääräinen reippaan ja rasittavan liikunnan (MVPA) minuutit päivässä (T3)

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

733 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist	format.spss	display_width
paAccelerometer_diff	Keskimääräinen reippaan ja rasittavan liikunnan (MVPA) minuutit päivässä (T3)	numeric	733	432	1165	-2.43	42.7	-127.11	-32.44	-3.23	22.98	167.2	<U+	2582><	U+2587> F8.2 0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

padaysLastweek_diff

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

283 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
padaysLastweek_diff	labelled	FALSE	0 (en yhtenäkään)=0,1=1,2=2,3=3,4=4,5=5,6=6,7=7	283	882	1165	15	0: 288, NA: 283, 1: 144, -1: 130	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

0 (en yhtenäkään): 0
1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
7: 7

pafreqUsually_diff

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

292 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
pafreqUsually_diff	labelled	FALSE	En voi vamman tai sairauden takia harrastaa liikuntaa=0,Harvemmin kuin kerran viikossa=1,1-2 kertaa viikossa=2,3 kertaa viikossa=3,4 kertaa viikossa=4,5 kertaa viikossa tai useammin=5	292	873	1165	9	0: 412, NA: 292, 1: 172, -1: 169	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

En voi vamman tai sairauden takia harrastaa liikuntaa: 0
Harvemmin kuin kerran viikossa: 1
1-2 kertaa viikossa: 2
3 kertaa viikossa: 3
4 kertaa viikossa: 4
5 kertaa viikossa tai useammin: 5

pahrsLastweek_diff

Kys0046.3: Yhteensä - Tuntia:

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

323 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
pahrsLastweek_diff	Kys0046.3: Yhteensä - Tuntia:	labelled	FALSE	0=1,1=2,2=3,3=4,4=5,5=6,6=7,7=8,8=9,9=10,10=11,11=12,12=13,13=14,14=15,15=16,16=17,17=18,18=19,19=20,20=21,21=22,22=23,23=24,24=25,25=26,26=27,27=28,28=29,29=30,30=31,31=32,32=33,33=34,34=35,35=36,36=37,37=38,38=39,39=40,40=41,41=42,42=43,43=44,44=45,45=46,46=47,47=48,48=49,49=50,50=51,51=52,52=53,53=54,54=55,55=56,56=57,57=58,58=59,59=60,60=61	323	842	1165	53	NA: 323, 0: 171, -1: 124, 1: 119	F2.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

pahrsUsually_diff

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

297 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
pahrsUsually_diff	labelled	FALSE	En yhtään=0,Noin puoli tuntia=1,Noin 1 tunnin=2,Noin 1,5 tuntia=3,Noin 2-3 tuntia=4,Noin 4-6 tuntia=5,Noin 7 tuntia tai enemmän=6	297	868	1165	13	NA: 297, 0: 294, -1: 171, 1: 169	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

En yhtään: 0
Noin puoli tuntia: 1
Noin 1 tunnin: 2
Noin 1,5 tuntia: 3
Noin 2-3 tuntia: 4
Noin 4-6 tuntia: 5
Noin 7 tuntia tai enemmän: 6

paminLastweek_diff

Kys0047.3: Yhteensä - Minuuttia:

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

488 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
paminLastweek_diff	Kys0047.3: Yhteensä - Minuuttia:	labelled	FALSE	0=1,30=2	488	677	1165	3	NA: 488, 0: 413, 1: 162, -1: 102	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

0: 1
30: 2

SB_dnorm_01_diff

Kys0178.3: yrittää rajoittaa omaa istumistaan KOULUPÄIVÄN aikana.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

319 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_dnorm_01_diff	Kys0178.3: yrittää rajoittaa omaa istumistaan KOULUPÄIVÄN aikana.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	319	846	1165	13	0: 341, NA: 319, 1: 97, 3: 90	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_dnorm_02_diff

Kys0179.3: yrittää rajoittaa omaa istumistaan VAPAA-AJALLA.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

324 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_dnorm_02_diff	Kys0179.3: yrittää rajoittaa omaa istumistaan VAPAA-AJALLA.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	324	841	1165	13	0: 327, NA: 324, 1: 102, 3: 84	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_inorm_01_diff

Kys0180.3: pitää hyväksyttävänä, että yritän rajoittaa omaa istumistani KOULUSSA.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

325 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_inorm_01_diff	Kys0180.3: pitää hyväksyttävänä, että yritän rajoittaa omaa istumistani KOULUSSA.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	325	840	1165	13	0: 346, NA: 325, 1: 97, 3: 97	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_inorm_02_diff

Kys0181.3: Suurin osa opettajistani hyväksyisi sen, jos rajoitan omaa istumistani KOULUSSA.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

330 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_inorm_02_diff	Kys0181.3: Suurin osa opettajistani hyväksyisi sen, jos rajoitan omaa istumistani KOULUSSA.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	330	835	1165	13	NA: 330, 0: 311, 1: 130, -1: 94	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_intention_01_diff

Kys0187.3: Aion rajoittaa omaa istumistani seuraavan kuukauden aikana KOULUSSA.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

321 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_intention_01_diff	Kys0187.3: Aion rajoittaa omaa istumistani seuraavan kuukauden aikana KOULUSSA.	labelled	FALSE	Epätodennäköistä1=1,2=2,3=3,4=4,5=5,6=6,Todennäköistä7=7	321	844	1165	13	NA: 321, 0: 274, 1: 140, -1: 117	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Epätodennäköistä1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Todennäköistä7: 7

SB_intention_02_diff

Kys0188.3: Aion rajoittaa omaa istumistani seuraavan kuukauden aikana KOULUSSA.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

326 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_intention_02_diff	Kys0188.3: Aion rajoittaa omaa istumistani seuraavan kuukauden aikana KOULUSSA.	labelled	FALSE	Ehdottomasti en1=1,2=2,3=3,4=4,5=5,6=6,Ehdottomasti kyllä7=7	326	839	1165	13	NA: 326, 0: 264, 1: 153, -1: 120	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ehdottomasti en1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Ehdottomasti kyllä7: 7

SB_intention_03_diff

Kys0189.3: Aion rajoittaa omaa istumistani seuraavan kuukauden aikana VAPAA-AJALLA.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

327 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_intention_03_diff	Kys0189.3: Aion rajoittaa omaa istumistani seuraavan kuukauden aikana VAPAA-AJALLA.	labelled	FALSE	Epätodennäköistä1=1,2=2,3=3,4=4,5=5,6=6,Todennäköistä7=7	327	838	1165	13	NA: 327, 0: 291, 1: 136, -1: 114	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Epätodennäköistä1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Todennäköistä7: 7

SB_intention_04_diff

Kys0190.3: Aion rajoittaa omaa istumistani seuraavan kuukauden aikana VAPAA-AJALLA.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

325 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_intention_04_diff	Kys0190.3: Aion rajoittaa omaa istumistani seuraavan kuukauden aikana VAPAA-AJALLA.	labelled	FALSE	Ehdottomasti en1=1,2=2,3=3,4=4,5=5,6=6,Ehdottomasti kyllä7=7	325	840	1165	13	NA: 325, 0: 277, 1: 155, -1: 130	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ehdottomasti en1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Ehdottomasti kyllä7: 7

SB_outcomeExpectationsNegative_01_diff

Kys0171.3: … oloni olisi epämukava.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

316 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_outcomeExpectationsNegative_01_diff	Kys0171.3: … oloni olisi epämukava.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	316	849	1165	13	NA: 316, 0: 277, -1: 111, -3: 96	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_outcomeExpectations_02_diff

Kys0172.3: … virkistyisin ja jaksaisin paremmin.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

326 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_outcomeExpectations_02_diff	Kys0172.3: … virkistyisin ja jaksaisin paremmin.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	326	839	1165	13	NA: 326, 0: 319, 1: 143, -1: 111	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_outcomeExpectations_03_diff

Kys0173.3: keskittymiskykyni paranisi.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

326 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_outcomeExpectations_03_diff	Kys0173.3: keskittymiskykyni paranisi.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	326	839	1165	13	NA: 326, 0: 292, 1: 158, -1: 106	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_outcomeExpectations_04_diff

Kys0174.3: niska-, hartia- ja selkäkivut sekä päänsäryt vähenisivät.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

319 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_outcomeExpectations_04_diff	Kys0174.3: niska-, hartia- ja selkäkivut sekä päänsäryt vähenisivät.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	319	846	1165	13	NA: 319, 0: 287, 1: 126, -1: 120	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_outcomeExpectations_05_diff

Kys0175.3: lihakseni eivät rappeutuisi.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

323 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_outcomeExpectations_05_diff	Kys0175.3: lihakseni eivät rappeutuisi.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	323	842	1165	13	NA: 323, 0: 304, 1: 144, -1: 102	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_outcomeExpectations_06_diff

Kys0176.3: aivoni toimisivat paremmin.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

322 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_outcomeExpectations_06_diff	Kys0176.3: aivoni toimisivat paremmin.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	322	843	1165	13	NA: 322, 0: 321, 1: 148, -1: 102	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_outcomeExpectationsNegative_07_diff

Kys0177.3: se häiritsisi asioiden tekemistä.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

323 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_outcomeExpectationsNegative_07_diff	Kys0177.3: se häiritsisi asioiden tekemistä.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	323	842	1165	13	NA: 323, 0: 282, -1: 112, 1: 100	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_sePbc_01_diff

Kys0182.3: Jos haluan, voin rajoittaa omaa istumistani KOULUSSA.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

321 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_sePbc_01_diff	Kys0182.3: Jos haluan, voin rajoittaa omaa istumistani KOULUSSA.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	321	844	1165	13	NA: 321, 0: 289, 1: 127, -1: 112	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_sePbc_02_diff

Kys0183.3: Voin itse täysin vaikuttaa siihen rajoitanko omaa istumistani KOULUSSA.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

321 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_sePbc_02_diff	Kys0183.3: Voin itse täysin vaikuttaa siihen rajoitanko omaa istumistani KOULUSSA.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	321	844	1165	13	NA: 321, 0: 277, 1: 127, -1: 117	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_sePbc_03_diff

Kys0184.3: Jos haluan, voin rajoittaa omaa istumistani VAPAA-AJALLA.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

321 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_sePbc_03_diff	Kys0184.3: Jos haluan, voin rajoittaa omaa istumistani VAPAA-AJALLA.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	321	844	1165	13	0: 404, NA: 321, -1: 106, 1: 98	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_sePbc_04_diff

Kys0185.3: Voin itse täysin vaikuttaa siihen rajoitanko omaa istumistani VAPAA-AJALLA.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

323 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_sePbc_04_diff	Kys0185.3: Voin itse täysin vaikuttaa siihen rajoitanko omaa istumistani VAPAA-AJALLA.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	323	842	1165	13	0: 393, NA: 323, -1: 109, 1: 94	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

SB_sePbc_05_diff

Kys0186.3: Jos haluan, voin rajoittaa omaa istumistani TYÖSSÄ OPPIMASSA.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

334 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
SB_sePbc_05_diff	Kys0186.3: Jos haluan, voin rajoittaa omaa istumistani TYÖSSÄ OPPIMASSA.	labelled	FALSE	Täysin eri mieltä1=1,2=2,3=3,Ei samaa eikä eri mieltä4=4,5=5,6=6,Täysin samaa mieltä7=7	334	831	1165	13	NA: 334, 0: 302, 1: 111, -1: 106	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Täysin eri mieltä1: 1
2: 2
3: 3
Ei samaa eikä eri mieltä4: 4
5: 5
6: 6
Täysin samaa mieltä7: 7

sitLieAccelerometer_diff

Keskimääräinen makuun ja istumisen (SB) aika päivässä (T3)

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

733 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist	format.spss	display_width
sitLieAccelerometer_diff	Keskimääräinen makuun ja istumisen (SB) aika päivässä (T3)	numeric	733	432	1165	-16.57	81.28	-298.72	-69.39	-19.43	32.97	309.6	<U+	2581><	U+2587> F8.2 0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

symptom_neckShoulderPain_diff

Kys0031.3: Niska- tai hartiakipuja

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

317 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
symptom_neckShoulderPain_diff	Kys0031.3: Niska- tai hartiakipuja	labelled	FALSE	Harvoin tai ei lainkaan=1,Noin kerran kuussa=2,Noin kerran viikossa=3,Lähes joka päivä=4	317	848	1165	7	0: 511, NA: 317, 1: 153, -1: 131	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Harvoin tai ei lainkaan: 1
Noin kerran kuussa: 2
Noin kerran viikossa: 3
Lähes joka päivä: 4

symptom_lowerBackPain_diff

Kys0032.3: Selän alaosan kipuja

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

314 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
symptom_lowerBackPain_diff	Kys0032.3: Selän alaosan kipuja	labelled	FALSE	Harvoin tai ei lainkaan=1,Noin kerran kuussa=2,Noin kerran viikossa=3,Lähes joka päivä=4	314	851	1165	7	0: 551, NA: 314, 1: 128, -1: 110	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Harvoin tai ei lainkaan: 1
Noin kerran kuussa: 2
Noin kerran viikossa: 3
Lähes joka päivä: 4

symptom_stomachAche_diff

Kys0033.3: Vatsakipuja

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

342 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
symptom_stomachAche_diff	Kys0033.3: Vatsakipuja	labelled	FALSE	Harvoin tai ei lainkaan=1,Noin kerran kuussa=2,Noin kerran viikossa=3,Lähes joka päivä=4	342	823	1165	7	0: 530, NA: 342, 1: 139, -1: 114	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Harvoin tai ei lainkaan: 1
Noin kerran kuussa: 2
Noin kerran viikossa: 3
Lähes joka päivä: 4

symptom_tensionNervousness_diff

Kys0034.3: Jännittyneisyyttä tai hermostuneisuutta

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

314 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
symptom_tensionNervousness_diff	Kys0034.3: Jännittyneisyyttä tai hermostuneisuutta	labelled	FALSE	Harvoin tai ei lainkaan=1,Noin kerran kuussa=2,Noin kerran viikossa=3,Lähes joka päivä=4	314	851	1165	7	0: 459, NA: 314, 1: 195, -1: 141	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Harvoin tai ei lainkaan: 1
Noin kerran kuussa: 2
Noin kerran viikossa: 3
Lähes joka päivä: 4

symptom_irritabilityAngerbursts_diff

Kys0035.3: Ärtyneisyyttä tai kiukunpurkauksia

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

325 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
symptom_irritabilityAngerbursts_diff	Kys0035.3: Ärtyneisyyttä tai kiukunpurkauksia	labelled	FALSE	Harvoin tai ei lainkaan=1,Noin kerran kuussa=2,Noin kerran viikossa=3,Lähes joka päivä=4	325	840	1165	6	0: 478, NA: 325, 1: 186, -1: 126	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Harvoin tai ei lainkaan: 1
Noin kerran kuussa: 2
Noin kerran viikossa: 3
Lähes joka päivä: 4

symptom_sleepDifficulty_diff

Kys0036.3: Vaikeuksia päästä uneen tai heräilemistä öisin

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

316 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
symptom_sleepDifficulty_diff	Kys0036.3: Vaikeuksia päästä uneen tai heräilemistä öisin	labelled	FALSE	Harvoin tai ei lainkaan=1,Noin kerran kuussa=2,Noin kerran viikossa=3,Lähes joka päivä=4	316	849	1165	7	0: 457, NA: 316, 1: 152, -1: 140	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Harvoin tai ei lainkaan: 1
Noin kerran kuussa: 2
Noin kerran viikossa: 3
Lähes joka päivä: 4

symptom_headAche_diff

Kys0037.3: Päänsärkyä

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

312 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
symptom_headAche_diff	Kys0037.3: Päänsärkyä	labelled	FALSE	Harvoin tai ei lainkaan=1,Noin kerran kuussa=2,Noin kerran viikossa=3,Lähes joka päivä=4	312	853	1165	7	0: 505, NA: 312, 1: 171, -1: 122	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Harvoin tai ei lainkaan: 1
Noin kerran kuussa: 2
Noin kerran viikossa: 3
Lähes joka päivä: 4

symptom_tirednessFaintness_diff

Kys0038.3: Väsymystä tai heikotusta

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

308 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
symptom_tirednessFaintness_diff	Kys0038.3: Väsymystä tai heikotusta	labelled	FALSE	Harvoin tai ei lainkaan=1,Noin kerran kuussa=2,Noin kerran viikossa=3,Lähes joka päivä=4	308	857	1165	7	0: 430, NA: 308, 1: 189, -1: 150	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Harvoin tai ei lainkaan: 1
Noin kerran kuussa: 2
Noin kerran viikossa: 3
Lähes joka päivä: 4

PA_agrbct_diff

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

301 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_agrbct_diff	numeric	301	864	1165	0.1	1.23	-5	-0.6	0.05	0.8	4.7

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_amotivation_diff

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

303 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_amotivation_diff	numeric	303	862	1165	0.084	0.82	-3.5	0	0	0.25	3

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_autonomous_diff

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

297 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_autonomous_diff	numeric	297	868	1165	0.035	0.75	-3.67	-0.33	0	0.44	3.67

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_controlled_diff

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

302 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_controlled_diff	numeric	302	863	1165	0.15	0.77	-4	-0.2	0	0.6	3.8

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_dnorm_diff

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

300 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_dnorm_diff	numeric	300	865	1165	-0.13	1.44	-6	-1	0	1	5

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_frqbct_diff

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

305 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_frqbct_diff	numeric	305	860	1165	0.18	1.11	-5.11	-0.44	0.11	0.78	4.22

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_goal_diff

Kys0147.3: Onko sinulla tällä hetkellä liikuntatavoite?

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

330 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_goal_diff	Kys0147.3: Onko sinulla tällä hetkellä liikuntatavoite?	labelled	FALSE	Kyllä (kerro lyhyesti, mikä tämänhetkinen liikuntatavoittees=0,Ei=1	330	835	1165	3	0: 600, NA: 330, 1: 143, -1: 92	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Kyllä (kerro lyhyesti, mikä tämänhetkinen liikuntatavoittees: 0
Ei: 1

PA_inorm_diff

Kys0108.3: Vanhempani haluaisivat minun liikkuvan säännöllisesti, vähintään 1,5 tuntia viik

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

304 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_inorm_diff	Kys0108.3: Vanhempani haluaisivat minun liikkuvan säännöllisesti, vähintään 1,5 tuntia viik	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,3=3,4=4,5=5,6=6,Pitää täysin paikkansa7=7	304	861	1165	13	0: 321, NA: 304, 1: 121, -1: 111	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
Pitää täysin paikkansa7: 7

PA_intention_diff

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

302 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_intention_diff	numeric	302	863	1165	-0.27	1.67	-6	-1	0	0.5	6

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_outcomeExpectations_diff

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

296 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_outcomeExpectations_diff	numeric	296	869	1165	0.071	0.91	-3.58	-0.42	0	0.5	5.55

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_opportunities_diff

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

297 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_opportunities_diff	numeric	297	868	1165	-0.27	0.89	-3.91	-0.79	-0.23	0.25	3.43

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_pbc_diff

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

298 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_pbc_diff	numeric	298	867	1165	-0.37	1.26	-4.67	-1	-0.33	0.33	4.33

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_selfefficacy_diff

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

297 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_selfefficacy_diff	numeric	297	868	1165	-0.27	1.46	-6	-1	0	0.5	5.5

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

SB_dnorm_diff

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

317 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
SB_dnorm_diff	numeric	317	848	1165	0.14	1.86	-6	-0.5	0	1	6

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

SB_inorm_diff

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

314 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
SB_inorm_diff	numeric	314	851	1165	0.26	1.51	-6	-0.5	0	1	6

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

SB_intention_diff

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

315 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
SB_intention_diff	numeric	315	850	1165	0.29	1.55	-5.75	-0.5	0	1	6

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

SB_outcomeExpectations_diff

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

314 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
SB_outcomeExpectations_diff	numeric	314	851	1165	0.048	1.18	-4.71	-0.57	0	0.71	5

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

SB_sePbc_diff

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

316 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
SB_sePbc_diff	numeric	316	849	1165	0.014	1.43	-6	-0.6	0	0.8	6

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

symptom_diff

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

276 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
symptom_diff	numeric	276	889	1165	0.064	0.46	-2	-0.12	0	0.25	3

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_actionplan_diff

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

302 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_actionplan_diff	numeric	302	863	1165	-0.054	0.91	-3	-0.5	0	0.25	3

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_copingplan_diff

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

301 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_copingplan_diff	numeric	301	864	1165	-0.03	0.87	-3	-0.5	0	0.5	3

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_sePbc_diff

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

297 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_sePbc_diff	numeric	297	868	1165	-0.32	1.07	-4.67	-0.92	-0.25	0.25	3.75

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_actCop_diff

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

301 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_actCop_diff	numeric	301	864	1165	-0.042	0.81	-3	-0.5	0	0.38	3

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_extrinsic_01_diff

Kys0080.3: koska muut ihmiset sanovat, että minun pitää liikkua.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

306 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_extrinsic_01_diff	Kys0080.3: koska muut ihmiset sanovat, että minun pitää liikkua.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	306	859	1165	9	0: 513, NA: 306, 1: 106, -1: 101	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_extrinsic_02_diff

Kys0081.3: koska muut ihmiset ovat tyytymättömiä minuun, jos en liiku.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

306 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_extrinsic_02_diff	Kys0081.3: koska muut ihmiset ovat tyytymättömiä minuun, jos en liiku.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	306	859	1165	9	0: 575, NA: 306, 1: 106, -1: 63	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_extrinsic_03_diff

Kys0083.3: koska kaverini ja perheeni painostavat minua liikkumaan.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

313 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_extrinsic_03_diff	Kys0083.3: koska kaverini ja perheeni painostavat minua liikkumaan.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	313	852	1165	9	0: 538, NA: 313, 1: 104, -1: 92	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_introjected_01_diff

Kys0084.3: koska tunnen syyllisyyttä, jos en liiku.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

309 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_introjected_01_diff	Kys0084.3: koska tunnen syyllisyyttä, jos en liiku.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	309	856	1165	9	0: 430, NA: 309, 1: 125, -1: 100	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_introjected_02_diff

Kys0085.3: koska tunnen itseni epäonnistuneeksi, jos en ole liikkunut vähään aikaan.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

309 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_introjected_02_diff	Kys0085.3: koska tunnen itseni epäonnistuneeksi, jos en ole liikkunut vähään aikaan.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	309	856	1165	9	0: 396, NA: 309, 1: 156, -1: 109	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_identified_01_diff

Kys0087.3: koska minusta on tärkeää nähdä vaivaa säännöllisen liikunnan eteen.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

314 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_identified_01_diff	Kys0087.3: koska minusta on tärkeää nähdä vaivaa säännöllisen liikunnan eteen.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	314	851	1165	9	0: 348, NA: 314, -1: 154, 1: 152	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_identified_02_diff

Kys0088.3: koska arvostan liikunnasta saamaani hyötyä.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

312 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_identified_02_diff	Kys0088.3: koska arvostan liikunnasta saamaani hyötyä.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	312	853	1165	9	0: 413, NA: 312, 1: 134, -1: 132	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_identified_03_diff

Kys0090.3: koska minulle on tärkeää liikkua säännöllisesti.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

310 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_identified_03_diff	Kys0090.3: koska minulle on tärkeää liikkua säännöllisesti.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	310	855	1165	9	0: 389, NA: 310, 1: 176, -1: 156	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_integrated_01_diff

Kys0089.3: koska se sopii yhteen elämäntavoitteideni kanssa.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

306 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_integrated_01_diff	Kys0089.3: koska se sopii yhteen elämäntavoitteideni kanssa.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	306	859	1165	9	0: 398, NA: 306, 1: 188, -1: 142	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_integrated_02_diff

Kys0092.3: …koska liikunta sopii yhteen arvojeni kanssa.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

312 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_integrated_02_diff	Kys0092.3: …koska liikunta sopii yhteen arvojeni kanssa.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	312	853	1165	9	0: 410, NA: 312, 1: 183, -1: 128	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_integrated_03_diff

Kys0094.3: koska liikunta on keskeinen osa sitä, kuka olen.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

310 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_integrated_03_diff	Kys0094.3: koska liikunta on keskeinen osa sitä, kuka olen.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	310	855	1165	9	0: 415, NA: 310, 1: 182, -1: 126	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_intrinsic_01_diff

Kys0091.3: koska tunnen iloa ja tyytyväisyyttä, kun liikun.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

306 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_intrinsic_01_diff	Kys0091.3: koska tunnen iloa ja tyytyväisyyttä, kun liikun.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	306	859	1165	9	0: 449, NA: 306, -1: 152, 1: 139	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_intrinsic_02_diff

Kys0093.3: koska liikkuminen on hauskaa.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

314 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_intrinsic_02_diff	Kys0093.3: koska liikkuminen on hauskaa.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	314	851	1165	9	0: 435, NA: 314, 1: 160, -1: 148	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_intrinsic_03_diff

Kys0095.3: koska nautin liikuntahetkistä.

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

321 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	label	data_type	ordered	value_labels	missing	complete	n	n_unique	top_counts	format.spss	display_width
PA_intrinsic_03_diff	Kys0095.3: koska nautin liikuntahetkistä.	labelled	FALSE	Ei pidä lainkaan paikkansa1=1,2=2,Pitää osittain paikkansa3=3,4=4,Pitää täysin paikkansa5=5	321	844	1165	9	0: 408, NA: 321, 1: 171, -1: 148	F1.0	0

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

Value labels

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

Ei pidä lainkaan paikkansa1: 1
2: 2
Pitää osittain paikkansa3: 3
4: 4
Pitää täysin paikkansa5: 5

PA_intrinsic_diff

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

300 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_intrinsic_diff	numeric	300	865	1165	0.026	0.87	-4	-0.33	0	0.33	4

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_integrated_diff

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

302 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_integrated_diff	numeric	302	863	1165	0.087	0.87	-4	-0.33	0	0.67	3

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_identified_diff

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

300 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_identified_diff	numeric	300	865	1165	-0.02	0.93	-3.67	-0.67	0	0.67	4

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_introjected_diff

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

302 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_introjected_diff	numeric	302	863	1165	0.21	1.14	-4	-0.25	0	1	4

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

PA_extrinsic_diff

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

305 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
PA_extrinsic_diff	numeric	305	860	1165	0.11	0.83	-4	0	0	0.33	3.67

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

trackSchool

Distribution

show_missings <- FALSE
if (haven::is.labelled(item)) {
  missings <- item[is.na(haven::zap_missing(item))]
  attributes(missings) <- attributes(item)
  if (!is.null(attributes(item)$labels)) {
    attributes(missings)$labels <- attributes(missings)$labels[is.na(attributes(missings)$labels)]
    attributes(item)$labels <- attributes(item)$labels[!is.na(attributes(item)$labels)]
  }
  if (is.numeric(item)) {
    show_missings <- length(unique(haven::na_tag(missings))) > 1
    item <- haven::zap_missing(item)
  }
  if (length(item_attributes$labels) == 0 && is.numeric(item)) {
    item <- haven::zap_labels(item)
  }
}
item_nomiss <- item[!is.na(item)]

# unnest mc_multiple and so on
if (
  is.character(item_nomiss) &&
  stringr::str_detect(item_nomiss, stringr::fixed(", ")) &&
  (exists("type", item_info) && 
    stringr::str_detect(item_info$type, pattern = stringr::fixed("multiple")))
  ) {
  item_nomiss <- unlist(stringr::str_split(item_nomiss, pattern = stringr::fixed(", ")))
}
attributes(item_nomiss) <- attributes(item)

old_height <- knitr::opts_chunk$get("fig.height")
non_missing_choices <- item_attributes[["labels"]]
many_labels <- length(non_missing_choices) > 7
go_vertical <- !is.numeric(item_nomiss) || many_labels
if ( go_vertical ) {
  # numeric items are plotted horizontally (because that's what usually expected)
  # categorical items are plotted vertically because we can use the screen real estate better this way

    if (is.null(choices) || 
        dplyr::n_distinct(item_nomiss) > length(non_missing_choices)) {
        non_missing_choices <- unique(item_nomiss)
        names(non_missing_choices) <- non_missing_choices
    }
  choice_multiplier <- old_height/6.5
    new_height <- 2 + choice_multiplier * length(non_missing_choices)
    new_height <- ifelse(new_height > 20, 20, new_height)
    new_height <- ifelse(new_height < 1, 1, new_height)
    knitr::opts_chunk$set(fig.height = new_height)
}

wrap_at <- knitr::opts_chunk$get("fig.width") * 10

# todo: if there are free-text choices mingled in with the pre-defined ones, don't show
# todo: show rare items if they are pre-defined
# todo: bin rare responses into "other category"
if (!length(item_nomiss)) {
  cat("No non-missing values to show.")
} else if (is.numeric(item_nomiss) || dplyr::n_distinct(item_nomiss) < 20) {
  plot_labelled(item_nomiss, item_name, wrap_at, go_vertical)
} else {
    cat(dplyr::n_distinct(item_nomiss), " unique, categorical values, so not shown.")
}

knitr::opts_chunk$set(fig.height = old_height)

0 missings.

Summary statistics

attributes(item) <- item_attributes
df = data.frame(item)
names(df) = html_item_name
knitr::kable(codebook_table(df), escape = TRUE)

name	data_type	ordered	missing	complete	n	n_unique	top_counts	V1	V2	V3	V4	V5	V6	V7	V8	V9	V10	V11	V12	V13	V14	V15	V16	V17
trackSchool	factor	FALSE	0	1165	1165	17	Nur: 277, BA1: 149, HRC: 145, BA2: 131	BA1	BA2	BA4	HRC1	HRC2	HRC5	IT1	IT2	NANA	Nur2	Nur3	Nur4	Other1	Other2	Other3	Other4	Other5

if (show_missings) {
  plot_labelled(missings, item_name, wrap_at)
}

if (!is.null(item_info)) {
  # don't show choices again, if they're basically same thing as value labels
  if (!is.null(choices) && !is.null(item_info$choices) && 
    all(names(na.omit(choices)) == item_info$choices) &&
    all(na.omit(choices) == names(item_info$choices))) {
    item_info$choices <- NULL
  }
  item_info$label_parsed <- 
    item_info$choice_list <- item_info$study_id <- item_info$id <- NULL
  pander::pander(item_info)
}

if (!is.null(choices) && length(choices) && length(choices) < 30) {
    pander::pander(as.list(choices))
}

missingness_report

Missingness report

Among those who finished the survey. Only variables that have missings are shown.

if (  exists("ended", results) &&
  exists("expired", results)) {
  finisher_results <- dplyr::filter(results, !is.na(.data$ended))
} else {
  finisher_results <- results
  warning("Could not figure out who finished the surveys, because the ",
          "variables expired and ended were missing.")
}

## Warning: Could not figure out who finished the surveys, because the
## variables expired and ended were missing.

if (length(md_pattern)) {
  pander::pander(md_pattern)
}

Table continues below
description	intervention	group	school	girl	track
Missings per variable	81	81	81	81	81
Missings in 0 variables	1	1	1	1	1
Missings in 4 variables	1	1	1	1	1
Missings in 2 variables	1	1	1	1	1
Missings in 304 variables	1	1	1	1	1
Missings in 308 variables	1	1	1	1	1
Missings in 7 variables	1	1	1	1	1
Missings in 307 variables	1	1	1	1	1
Missings in 8 variables	1	1	1	1	1
Missings in 5 variables	1	1	1	1	1
Missings in 330 variables	0	0	0	0	0
Missings in 6 variables	1	1	1	1	1
Missings in 9 variables	1	1	1	1	1
581 other, less frequent patterns	533	533	533	533	533

Table continues below
symptom_T1	padaysLastweek_T1	pafreqUsually_T1	pahrsLastweek_T1
81	83	83	83
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
533	531	531	531

Table continues below
pahrsUsually_T1	paminLastweek_T1	paLastweek_T1	PA_autonomous_T1
83	83	83	87
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
531	531	531	527

Table continues below
PA_outcomeExpectations_T1	PA_opportunities_T1	PA_intrinsic_T1
87	90	91
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
527	524	523

Table continues below
PA_identified_T1	PA_actplan_01_T1	PA_actplan_02_T1	PA_actplan_03_T1
91	92	92	92
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
523	522	522	522

Table continues below
PA_actplan_04_T1	PA_copplan_01_T1	PA_copplan_02_T1	PA_copplan_03_T1
92	92	92	92
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
522	522	522	522

Table continues below
PA_copplan_04_T1	PA_dnorm_02_T1	PA_dnorm_01_T1	PA_inorm_01_T1
92	92	92	92
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
522	522	522	522

Table continues below
PA_intention_01_T1	PA_intention_02_T1	PA_controlled_T1	PA_dnorm_T1
92	92	92	92
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
522	522	522	522

Table continues below
PA_inorm_T1	PA_intention_T1	PA_actionplan_T1	PA_copingplan_T1
92	92	92	92
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
522	522	522	522

Table continues below
PA_actCop_T1	PA_integrated_T1	PA_introjected_T1	PA_amotivation_T1
92	92	92	93
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
522	522	522	521

Table continues below
PA_agrbct_01_T1	PA_agrbct_02_T1	PA_agrbct_03_T1	PA_agrbct_04_T1
94	94	94	94
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
520	520	520	520

Table continues below
PA_agrbct_05_T1	PA_agrbct_06_T1	PA_agrbct_07_T1	PA_agrbct_08_T1
94	94	94	94
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
520	520	520	520

Table continues below
PA_agrbct_09_T1	PA_agrbct_10_T1	PA_outcomeExpectations_01_T1
94	94	94
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
520	520	520

Table continues below
PA_outcomeExpectations_04_T1	PA_outcomeExpectations_06_T1
94	94
1	1
1	1
1	1
1	1
1	1
1	1
1	1
1	1
1	1
0	0
1	1
1	1
520	520

Table continues below
PA_selfefficacy_01_T1	PA_selfefficacyReverseCoded_02_T1	PA_agrbct_T1
94	94	94
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
520	520	520

Table continues below
PA_pbc_T1	PA_selfefficacy_T1	PA_sePbc_T1	PA_frqbct_01_T1
94	94	94	95
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
520	520	520	519

Table continues below
PA_frqbct_02_T1	PA_frqbct_03_T1	PA_frqbct_04_T1	PA_frqbct_05_T1
95	95	95	95
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
519	519	519	519

Table continues below
PA_frqbct_06_T1	PA_frqbct_07_T1	PA_frqbct_08_T1	PA_frqbct_09_T1
95	95	95	95
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
519	519	519	519

Table continues below
PA_autonomous_03_T1	PA_autonomous_04_T1	PA_autonomous_07_T1
95	95	95
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
519	519	519

Table continues below
PA_outcomeExpectations_12_T1	PA_opportunities_01_T1	PA_opportunities_04_T1
95	95	95
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
519	519	519

Table continues below
PA_frqbct_T1	PA_identified_03_T1	PA_integrated_01_T1	PA_intrinsic_01_T1
95	95	95	95
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
519	519	519	519

Table continues below
PA_controlled_02_T1	PA_outcomeExpectations_10_T1	PA_pbc_01_T1
96	96	96
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
518	518	518

Table continues below
PA_extrinsic_02_T1	PA_extrinsic_T1	PA_controlled_01_T1
96	96	97
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
518	518	517

Table continues below
PA_controlled_04_T1	PA_opportunities_07_T1	PA_extrinsic_01_T1
97	97	97
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
517	517	517

Table continues below
PA_introjected_01_T1	PA_amotivation_03_T1	PA_outcomeExpectations_05_T1
97	98	98
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
517	516	516

Table continues below
PA_opportunities_02_T1	big5openReverseCoded_02_T1	PA_amotivation_04_T1
98	99	99
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
516	515	515

Table continues below
PA_autonomous_06_T1	PA_autonomous_08_T1	PA_controlled_05_T1
99	99	99
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
515	515	515

Table continues below
PA_outcomeExpectationsNegative_02_T1	PA_opportunitiesReverseCoded_08_T1
99	99
1	1
1	1
1	1
1	1
1	1
1	1
1	1
1	1
1	1
0	0
1	1
1	1
515	515

Table continues below
PA_pbc_03_T1	PA_introjected_02_T1	PA_integrated_03_T1	PA_intrinsic_02_T1
99	99	99	99
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
515	515	515	515

Table continues below
big5consReverseCoded_02_T1	PA_opportunitiesReverseCoded_03_T1
100	100
1	1
1	1
1	1
1	1
1	1
1	1
1	1
1	1
1	1
0	0
1	1
1	1
514	514

Table continues below
big5agrReverseCoded_02_T1	big5neuroticism_01_T1	PA_controlled_03_T1
101	101	101
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
513	513	513

Table continues below
PA_outcomeExpectations_03_T1	PA_outcomeExpectationsNegative_09_T1
101	101
1	1
1	1
1	1
1	1
1	1
1	1
1	1
1	1
1	1
0	0
1	1
1	1
516	513

Table continues below
PA_opportunities_05_T1	big5neuroticism_T1	SB_inorm_T1	SB_intention_T1
101	101	101	101
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
513	513	513	513

Table continues below
SB_outcomeExpectations_T1	SB_sePbc_T1	PA_extrinsic_03_T1
101	101	101
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
513	513	513

Table continues below
big5extraversion_01_T1	PA_autonomous_01_T1	PA_autonomous_02_T1
102	102	102
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
512	512	512

Table continues below
PA_outcomeExpectations_11_T1	PA_outcomeExpectationsNegative_08_T1
102	102
1	1
1	1
1	1
1	1
1	1
1	1
1	1
1	1
1	1
0	0
1	1
1	1
513	512

Table continues below
PA_pbcReverseCoded_02_T1	SB_outcomeExpectationsNegative_01_T1
102	102
1	1
1	1
1	1
1	1
1	1
1	1
1	1
1	1
1	1
0	0
1	1
1	1
512	512

Table continues below
SB_outcomeExpectations_04_T1	big5extraversion_T1	PA_identified_01_T1
102	102	102
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
512	512	512

Table continues below
PA_identified_02_T1	big5extReverseCoded_02_T1	big5openness_01_T1
102	103	103
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
512	511	511

Table continues below
PA_amotivation_01_T1	PA_autonomous_05_T1	PA_outcomeExpectations_07_T1
103	103	103
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
511	511	511

Table continues below
SB_sePbc_01_T1	big5openness_T1	SB_dnorm_T1	PA_integrated_02_T1
103	103	103	103
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
511	511	511	511

Table continues below
big5agreeableness_01_T1	big5neurReverseCoded_02_T1	PA_goal_01_T1
104	104	104
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
512	510	510

Table continues below
SB_sePbc_02_T1	big5agreeableness_T1	PA_goal_T1	SB_dnorm_02_T1
104	104	104	105
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
510	512	510	509

Table continues below
SB_outcomeExpectations_05_T1	SB_sePbc_03_T1	SB_sePbc_04_T1
105	105	105
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
509	509	509

Table continues below
big5conscientiousness_01_T1	PA_opportunitiesReverseCoded_06_T1
106	106
1	1
1	1
1	1
1	1
1	1
1	1
1	1
1	1
1	1
0	0
1	1
1	1
508	508

Table continues below
SB_dnorm_01_T1	SB_intention_01_T1	big5conscientiousness_T1
106	106	106
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
508	508	508

Table continues below
SB_outcomeExpectations_03_T1	SB_outcomeExpectations_06_T1
107	107
1	1
1	1
1	1
1	1
1	1
1	1
1	1
1	1
1	1
0	0
1	1
1	1
507	507

Table continues below
symptom_tirednessFaintness_T1	PA_amotivation_02_T1	PA_autonomous_09_T1
107	108	108
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
507	507	507

Table continues below
SB_outcomeExpectationsNegative_07_T1	PA_intrinsic_03_T1	SB_inorm_01_T1
108	108	109
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
506	507	506

Table continues below
SB_intention_02_T1	SB_outcomeExpectations_02_T1	SB_intention_04_T1
109	109	110
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
505	505	505

Table continues below
symptom_headAche_T1	SB_intention_03_T1	SB_sePbc_05_T1	SB_inorm_02_T1
110	111	111	112
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
504	503	504	502

Table continues below
symptom_lowerBackPain_T1	symptom_sleepDifficulty_T1
112	113
1	1
1	1
1	1
1	1
1	1
1	1
1	1
1	1
1	1
0	0
1	1
1	1
502	501

Table continues below
symptom_tensionNervousness_T1	symptom_neckShoulderPain_T1
114	118
1	1
1	1
1	1
1	1
1	1
1	1
1	1
1	1
1	1
0	0
1	1
1	1
500	496

Table continues below
symptom_irritabilityAngerbursts_T1	symptom_stomachAche_T1	fatpct_T1
126	139	203
1	1	1
1	1	1
1	1	1
1	1	1
1	1	0
1	1	1
1	1	1
1	1	0
1	1	1
0	0	0
1	1	1
1	1	1
488	484	477

Table continues below
symptom_T3	padaysLastweek_T3	PA_selfefficacy_T3	PA_sePbc_T3
216	221	228	228
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
0	0	0	0
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
508	506	499	499

Table continues below
PA_opportunities_07_T3	PA_selfefficacyReverseCoded_02_T3
229	229
1	1
1	1
1	1
0	0
0	0
1	1
0	0
1	1
1	1
1	1
1	1
1	1
498	498

Table continues below
PA_outcomeExpectations_T3	PA_opportunities_T3	pafreqUsually_T3
229	229	231
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
498	498	496

Table continues below
symptom_headAche_T3	PA_pbc_T3	PA_pbc_01_T3	symptom_tirednessFaintness_T3
231	231	232	232
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
0	0	0	0
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
493	496	495	492

Table continues below
PA_outcomeExpectations_01_T3	PA_opportunities_04_T3
233	233
1	1
1	1
1	1
0	0
0	0
1	1
0	0
1	1
1	1
1	1
1	1
1	1
494	494

Table continues below
PA_opportunitiesReverseCoded_06_T3	PA_agrbct_T3	PA_autonomous_T3
233	233	233
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
494	494	494

Table continues below
PA_dnorm_T3	PA_copingplan_T3	PA_actCop_T3	PA_copplan_01_T3
233	233	233	234
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
0	0	0	0
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
494	494	494	493

Table continues below
PA_dnorm_01_T3	PA_outcomeExpectationsNegative_08_T3
234	234
1	1
1	1
1	1
0	0
0	0
1	1
0	0
1	1
1	1
1	1
1	1
1	1
493	493

Table continues below
PA_pbcReverseCoded_02_T3	PA_selfefficacy_01_T3
234	234
1	1
1	1
1	1
0	0
0	0
1	1
0	0
1	1
1	1
1	1
1	1
1	1
493	493

Table continues below
symptom_tensionNervousness_T3	PA_amotivation_T3	PA_intention_T3
234	234	234
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
490	493	493

Table continues below
PA_identified_T3	PA_outcomeExpectations_05_T3	PA_opportunities_01_T3
234	235	235
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
493	492	492

Table continues below
PA_opportunities_02_T3	PA_opportunities_05_T3
235	235
1	1
1	1
1	1
0	0
0	0
1	1
0	0
1	1
1	1
1	1
1	1
1	1
492	493

Table continues below
PA_opportunitiesReverseCoded_03_T3	PA_pbc_03_T3
235	235
1	1
1	1
1	1
0	0
0	0
1	1
0	0
1	1
1	1
1	1
1	1
1	1
492	492

Table continues below
symptom_neckShoulderPain_T3	PA_controlled_T3	PA_actionplan_T3
235	235	235
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
490	492	492

Table continues below
PA_introjected_T3	PA_amotivation_04_T3	PA_copplan_02_T3
235	236	236
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
492	491	491

Table continues below
PA_outcomeExpectations_04_T3	pahrsUsually_T3	symptom_sleepDifficulty_T3
236	236	236
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
491	493	489

Table continues below
PA_intrinsic_T3	PA_integrated_T3	PA_agrbct_01_T3	PA_copplan_03_T3
236	236	237	237
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
0	0	0	0
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
491	491	490	490

Table continues below
PA_controlled_01_T3	PA_frqbct_01_T3	PA_outcomeExpectations_06_T3
237	237	237
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
490	490	490

Table continues below
PA_outcomeExpectations_10_T3	PA_frqbct_T3	PA_extrinsic_01_T3
237	237	237
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
490	490	490

Table continues below
PA_extrinsic_T3	PA_agrbct_04_T3	PA_dnormparents_02_T3	PA_inorm_01_T3
237	238	238	238
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
0	0	0	0
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
490	489	489	489

Table continues below
PA_outcomeExpectations_11_T3	PA_outcomeExpectationsNegative_02_T3
238	238
1	1
1	1
1	1
0	0
0	0
1	1
0	0
1	1
1	1
1	1
1	1
1	1
489	489

Table continues below
PA_inorm_T3	PA_agrbct_03_T3	PA_agrbct_05_T3	PA_controlled_02_T3
238	239	239	239
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
0	0	0	0
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
489	488	488	488

Table continues below
PA_autonomous_04_T3	PA_autonomous_05_T3	PA_controlled_05_T3
239	239	239
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
488	488	488

Table continues below
PA_outcomeExpectations_03_T3	PA_outcomeExpectations_07_T3
239	239
1	1
1	1
1	1
0	0
0	0
1	1
0	0
1	1
1	1
1	1
1	1
1	1
488	488

Table continues below
PA_outcomeExpectationsNegative_09_T3	symptom_irritabilityAngerbursts_T3
239	239
1	1
1	1
1	1
0	0
0	0
1	1
0	0
1	1
1	1
1	1
1	1
1	1
488	485

Table continues below
PA_extrinsic_02_T3	PA_introjected_02_T3	PA_integrated_01_T3
239	239	239
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
488	488	488

Table continues below
PA_integrated_02_T3	PA_agrbct_02_T3	PA_agrbct_09_T3	PA_autonomous_02_T3
239	240	240	240
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
0	0	0	0
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
488	487	487	487

Table continues below
symptom_lowerBackPain_T3	PA_identified_02_T3	PA_autonomous_01_T3
240	240	241
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
485	487	486

Table continues below
PA_autonomous_06_T3	PA_intention_02_T3	PA_autonomous_07_T3
241	241	241
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
486	486	486

Table continues below
PA_identified_01_T3	PA_integrated_03_T3	PA_intrinsic_01_T3
241	241	241
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
486	486	486

Table continues below
PA_agrbct_08_T3	PA_autonomous_08_T3	PA_intrinsic_02_T3	PA_actplan_01_T3
242	242	242	243
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
0	0	0	0
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
485	485	485	484

Table continues below
PA_copplan_04_T3	PA_frqbct_02_T3	PA_frqbct_03_T3	PA_frqbct_07_T3
243	243	243	243
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
0	0	0	0
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
485	484	484	485

Table continues below
PA_frqbct_08_T3	PA_outcomeExpectations_12_T3	PA_actplan_04_T3
243	243	244
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
484	484	483

Table continues below
PA_agrbct_10_T3	PA_amotivation_01_T3	PA_controlled_03_T3
244	244	244
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
483	483	483

Table continues below
PA_autonomous_03_T3	PA_controlled_04_T3	PA_extrinsic_03_T3
244	244	244
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
483	483	483

Table continues below
PA_introjected_01_T3	PA_identified_03_T3	PA_actplan_02_T3
244	244	245
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
483	483	482

Table continues below
PA_amotivation_03_T3	PA_intention_01_T3	PA_amotivation_02_T3
245	245	246
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
482	483	481

Table continues below
PA_frqbct_04_T3	PA_autonomous_09_T3	PA_intrinsic_03_T3	PA_actplan_03_T3
246	247	247	248
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
0	0	0	0
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
481	480	480	480

Table continues below
PA_agrbct_06_T3	PA_agrbct_07_T3	SB_inorm_T3	SB_intention_T3
248	248	248	248
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
0	0	0	0
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
479	479	480	480

Table continues below
SB_outcomeExpectations_T3	PA_frqbct_06_T3	SB_dnorm_01_T3
248	249	249
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
480	478	479

Table continues below
symptom_stomachAche_T3	SB_dnorm_T3	SB_sePbc_T3	PA_frqbct_05_T3
249	249	249	250
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
0	0	0	0
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
475	479	479	477

Table continues below
SB_outcomeExpectationsNegative_01_T3	PA_frqbct_09_T3	SB_inorm_01_T3
250	252	252
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
478	476	477

Table continues below
SB_intention_01_T3	SB_intention_04_T3	SB_outcomeExpectationsNegative_07_T3
252	252	252
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
476	476	476

Table continues below
SB_sePbc_02_T3	SB_sePbc_03_T3	SB_intention_03_T3
252	252	253
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
476	476	476

Table continues below
SB_outcomeExpectations_04_T3	SB_sePbc_01_T3	SB_sePbc_04_T3
253	253	253
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
475	475	475

Table continues below
SB_intention_02_T3	SB_outcomeExpectations_02_T3
254	254
1	1
1	1
1	1
0	0
0	0
1	1
0	0
1	1
1	1
1	1
1	1
1	1
474	474

Table continues below
SB_outcomeExpectations_05_T3	SB_dnorm_02_T3	SB_outcomeExpectations_03_T3
254	255	256
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
1	1	1
1	1	1
1	1	1
474	473	472

Table continues below
SB_outcomeExpectations_06_T3	PA_goal_01_T3	SB_inorm_02_T3	PA_goal_T3
256	257	257	257
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
0	0	0	0
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
472	471	472	471

Table continues below
SB_sePbc_05_T3	pahrsLastweek_T3	symptom_diff	padaysLastweek_diff
259	264	276	283
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
0	0	0	0
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
1	1	0	0
1	1	1	1
1	1	1	1
471	474	465	461

Table continues below
pafreqUsually_diff	PA_outcomeExpectations_diff	pahrsUsually_diff
292	296	297
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
452	448	449

Table continues below
PA_autonomous_diff	PA_opportunities_diff	PA_selfefficacy_diff
297	297	297
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
447	447	447

Table continues below
PA_sePbc_diff	PA_selfefficacyReverseCoded_02_diff	PA_pbc_diff
297	298	298
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
447	446	446

Table continues below
PA_pbc_01_diff	PA_dnorm_diff	PA_intrinsic_diff	PA_identified_diff
300	300	300	300
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
0	0	0	0
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
444	444	444	444

Table continues below
PA_copplan_01_diff	PA_dnorm_01_diff	PA_agrbct_diff	PA_copingplan_diff
301	301	301	301
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
0	0	0	0
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
443	443	443	443

Table continues below
PA_actCop_diff	PA_opportunities_04_diff	PA_selfefficacy_01_diff
301	302	302
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
443	442	442

Table continues below
PA_controlled_diff	PA_intention_diff	PA_actionplan_diff
302	302	302
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
442	442	442

Table continues below
PA_integrated_diff	PA_introjected_diff	PA_copplan_02_diff
302	302	303
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
442	442	441

Table continues below
PA_dnorm_02_diff	PA_opportunities_07_diff	PA_amotivation_diff
303	303	303
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
441	441	441

Table continues below
PA_agrbct_01_diff	PA_agrbct_04_diff	PA_copplan_03_diff	PA_inorm_01_diff
304	304	304	304
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
0	0	0	0
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
440	440	440	440

Table continues below
PA_outcomeExpectations_01_diff	PA_pbc_03_diff	PA_inorm_diff
304	304	304
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
440	440	440

Table continues below
PA_agrbct_05_diff	PA_frqbct_01_diff	PA_outcomeExpectations_04_diff
305	305	305
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
439	439	439

Table continues below
PA_frqbct_diff	PA_extrinsic_diff	PA_agrbct_02_diff	PA_agrbct_03_diff
305	305	306	306
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
0	0	0	0
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
439	439	438	438

Table continues below
PA_controlled_01_diff	PA_controlled_02_diff	PA_autonomous_04_diff
306	306	306
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
438	438	438

Table continues below
PA_autonomous_07_diff	PA_opportunities_01_diff	PA_opportunities_02_diff
306	306	306
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
438	438	438

Table continues below
PA_pbcReverseCoded_02_diff	PA_extrinsic_01_diff	PA_extrinsic_02_diff
306	306	306
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
438	438	438

Table continues below
PA_integrated_01_diff	PA_intrinsic_01_diff	PA_agrbct_08_diff
306	306	307
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
438	438	437

Table continues below
PA_agrbct_09_diff	PA_copplan_04_diff	PA_intention_02_diff
307	307	307
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
437	438	437

Table continues below
PA_outcomeExpectations_05_diff	PA_outcomeExpectations_06_diff
307	307
1	1
1	1
1	1
0	0
0	0
1	1
0	0
1	1
1	1
0	0
1	1
1	1
437	437

Table continues below
PA_outcomeExpectations_10_diff	PA_amotivation_04_diff
307	308
1	1
1	1
1	1
0	0
0	0
1	1
0	0
1	1
1	1
0	0
1	1
1	1
437	436

Table continues below
symptom_tirednessFaintness_diff	PA_actplan_01_diff	PA_frqbct_02_diff
308	309	309
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
433	435	435

Table continues below
PA_frqbct_03_diff	PA_frqbct_08_diff	PA_controlled_04_diff
309	309	309
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
435	435	435

Table continues below
PA_controlled_05_diff	PA_outcomeExpectationsNegative_08_diff
309	309
1	1
1	1
1	1
0	0
0	0
1	1
0	0
1	1
1	1
0	0
1	1
1	1
435	435

Table continues below
PA_opportunities_05_diff	PA_opportunitiesReverseCoded_03_diff
309	309
1	1
1	1
1	1
0	0
0	0
1	1
0	0
1	1
1	1
0	0
1	1
1	1
436	435

Table continues below
PA_introjected_01_diff	PA_introjected_02_diff	PA_actplan_04_diff
309	309	310
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
435	435	434

Table continues below
PA_agrbct_10_diff	PA_frqbct_07_diff	PA_autonomous_03_diff
310	310	310
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
434	435	434

Table continues below
PA_autonomous_06_diff	PA_identified_03_diff	PA_integrated_03_diff
310	310	310
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
434	434	434

Table continues below
PA_actplan_02_diff	PA_frqbct_04_diff	PA_intention_01_diff
311	311	311
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
433	433	434

Table continues below
PA_outcomeExpectations_12_diff	PA_outcomeExpectationsNegative_02_diff
311	311
1	1
1	1
1	1
0	0
0	0
1	1
0	0
1	1
1	1
0	0
1	1
1	1
433	433

Table continues below
PA_agrbct_07_diff	PA_amotivation_03_diff	PA_autonomous_02_diff
312	312	312
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
432	432	432

Table continues below
PA_autonomous_05_diff	PA_opportunitiesReverseCoded_06_diff
312	312
1	1
1	1
1	1
0	0
0	0
1	1
0	0
1	1
1	1
0	0
1	1
1	1
432	432

Table continues below
symptom_headAche_diff	PA_identified_02_diff	PA_integrated_02_diff
312	312	312
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
429	432	432

Table continues below
PA_actplan_03_diff	PA_controlled_03_diff	PA_frqbct_06_diff
313	313	313
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
432	431	431

Table continues below
PA_outcomeExpectations_07_diff	PA_outcomeExpectations_11_diff
313	313
1	1
1	1
1	1
0	0
0	0
1	1
0	0
1	1
1	1
0	0
1	1
1	1
431	431

Table continues below
PA_extrinsic_03_diff	PA_agrbct_06_diff	PA_frqbct_05_diff
313	314	314
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
431	430	430

Table continues below
PA_autonomous_01_diff	PA_autonomous_08_diff	PA_outcomeExpectations_03_diff
314	314	314
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
430	430	433

Table continues below
PA_outcomeExpectationsNegative_09_diff	symptom_lowerBackPain_diff
314	314
1	1
1	1
1	1
0	0
0	0
1	1
0	0
1	1
1	1
0	0
1	1
1	1
430	428

Table continues below
symptom_tensionNervousness_diff	SB_inorm_diff	SB_outcomeExpectations_diff
314	314	314
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
427	431	431

Table continues below
PA_identified_01_diff	PA_intrinsic_02_diff	SB_intention_diff
314	314	315
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
430	430	430

Table continues below
SB_outcomeExpectationsNegative_01_diff	symptom_sleepDifficulty_diff
316	316
1	1
1	1
1	1
0	0
0	0
1	1
0	0
1	1
1	1
0	0
1	1
1	1
429	426

Table continues below
SB_sePbc_diff	PA_amotivation_01_diff	PA_frqbct_09_diff
316	317	317
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
429	427	428

Table continues below
symptom_neckShoulderPain_diff	SB_dnorm_diff	PA_amotivation_02_diff
317	317	318
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
425	428	426

Table continues below
SB_dnorm_01_diff	SB_outcomeExpectations_04_diff	PA_autonomous_09_diff
319	319	321
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
426	426	423

Table continues below
SB_intention_01_diff	SB_sePbc_01_diff	SB_sePbc_02_diff	SB_sePbc_03_diff
321	321	321	321
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
0	0	0	0
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
424	424	424	424

Table continues below
PA_intrinsic_03_diff	SB_outcomeExpectations_06_diff	pahrsLastweek_diff
321	322	323
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
0	0	0
1	1	1
1	1	1
423	423	432

Table continues below
SB_outcomeExpectations_05_diff	SB_outcomeExpectationsNegative_07_diff
323	323
1	1
1	1
1	1
0	0
0	0
1	1
0	0
1	1
1	1
0	0
1	1
1	1
422	422

Table continues below
SB_sePbc_04_diff	SB_dnorm_02_diff	SB_inorm_01_diff	SB_intention_04_diff
323	324	325	325
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
0	0	0	0
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
422	421	422	421

Table continues below
symptom_irritabilityAngerbursts_diff	SB_intention_02_diff
325	326
1	1
1	1
1	1
0	0
0	0
1	1
0	0
1	1
1	1
0	0
1	1
1	1
416	419

Table continues below
SB_outcomeExpectations_02_diff	SB_outcomeExpectations_03_diff
326	326
1	1
1	1
1	1
0	0
0	0
1	1
0	0
1	1
1	1
0	0
1	1
1	1
419	419

Table continues below
SB_intention_03_diff	PA_goal_01_diff	SB_inorm_02_diff	PA_goal_diff
327	330	330	330
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
0	0	0	0
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
419	415	416	415

Table continues below
SB_sePbc_05_diff	symptom_stomachAche_diff	paminLastweek_T3
334	342	440
1	1	1
1	1	1
1	1	0
0	0	0
0	0	0
1	1	1
0	0	0
1	1	1
1	1	1
0	0	1
1	1	0
1	1	0
414	407	378

Table continues below
paAccelerometer_T1	sitLieAccelerometer_T1	sitBreaks_T1
452	452	452
1	1	1
1	1	1
1	1	1
1	1	1
0	0	0
0	0	0
0	0	0
0	0	0
0	0	0
0	0	0
1	1	1
0	0	0
339	339	339

Table continues below
paminLastweek_diff	paAccelerometer_T3	sitLieAccelerometer_T3
488	657	657
1	1	1
1	0	0
0	1	1
0	0	0
0	0	0
1	0	0
0	0	0
1	0	0
1	1	1
0	0	0
0	0	0
0	0	0
345	242	242

paAccelerometer_diff	sitLieAccelerometer_diff	var_miss	n_miss
733	733	104270	104270
1	1	0	156
0	0	4	62
1	1	2	47
0	0	304	44
0	0	308	40
0	0	7	38
0	0	307	30
0	0	8	21
0	0	5	14
0	0	330	13
0	0	6	12
0	0	9	12
191	191	49922	676

items

Codebook table

export_table(metadata_table)

jsonld

print("öäa??????")

## [1] "öäa??????"

symptom_T1	padaysLastweek_T1	pafreqUsually_T1	pahrsLastweek_T1
81	83	83	83
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
533	531	531	531

pahrsUsually_T1	paminLastweek_T1	paLastweek_T1	PA_autonomous_T1
83	83	83	87
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
531	531	531	527

PA_identified_T1	PA_actplan_01_T1	PA_actplan_02_T1	PA_actplan_03_T1
91	92	92	92
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
523	522	522	522

PA_actplan_04_T1	PA_copplan_01_T1	PA_copplan_02_T1	PA_copplan_03_T1
92	92	92	92
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
522	522	522	522

PA_copplan_04_T1	PA_dnorm_02_T1	PA_dnorm_01_T1	PA_inorm_01_T1
92	92	92	92
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
522	522	522	522

PA_intention_01_T1	PA_intention_02_T1	PA_controlled_T1	PA_dnorm_T1
92	92	92	92
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
522	522	522	522

PA_inorm_T1	PA_intention_T1	PA_actionplan_T1	PA_copingplan_T1
92	92	92	92
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
522	522	522	522

PA_actCop_T1	PA_integrated_T1	PA_introjected_T1	PA_amotivation_T1
92	92	92	93
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
522	522	522	521

PA_agrbct_01_T1	PA_agrbct_02_T1	PA_agrbct_03_T1	PA_agrbct_04_T1
94	94	94	94
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
520	520	520	520

PA_agrbct_05_T1	PA_agrbct_06_T1	PA_agrbct_07_T1	PA_agrbct_08_T1
94	94	94	94
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
520	520	520	520

symptom_T1	padaysLastweek_T1	pafreqUsually_T1	pahrsLastweek_T1
81	83	83	83
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
533	531	531	531

pahrsUsually_T1	paminLastweek_T1	paLastweek_T1	PA_autonomous_T1
83	83	83	87
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
531	531	531	527

PA_identified_T1	PA_actplan_01_T1	PA_actplan_02_T1	PA_actplan_03_T1
91	92	92	92
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
523	522	522	522

PA_actplan_04_T1	PA_copplan_01_T1	PA_copplan_02_T1	PA_copplan_03_T1
92	92	92	92
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
522	522	522	522

PA_copplan_04_T1	PA_dnorm_02_T1	PA_dnorm_01_T1	PA_inorm_01_T1
92	92	92	92
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
522	522	522	522

PA_intention_01_T1	PA_intention_02_T1	PA_controlled_T1	PA_dnorm_T1
92	92	92	92
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
522	522	522	522

PA_inorm_T1	PA_intention_T1	PA_actionplan_T1	PA_copingplan_T1
92	92	92	92
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
522	522	522	522

PA_actCop_T1	PA_integrated_T1	PA_introjected_T1	PA_amotivation_T1
92	92	92	93
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
522	522	522	521

PA_agrbct_01_T1	PA_agrbct_02_T1	PA_agrbct_03_T1	PA_agrbct_04_T1
94	94	94	94
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
520	520	520	520

PA_agrbct_05_T1	PA_agrbct_06_T1	PA_agrbct_07_T1	PA_agrbct_08_T1
94	94	94	94
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
520	520	520	520

Codebook

Matti Heino

20 kesäkuuta 2018

Items

id

Distribution

Summary statistics

intervention

Distribution

Summary statistics

group

Distribution

Summary statistics

school

Distribution

Summary statistics

girl

Distribution

Summary statistics

track

Distribution

Summary statistics

big5agreeableness_01_T1

Distribution

Summary statistics

Value labels

big5agrReverseCoded_02_T1

Distribution

Summary statistics

Value labels

big5conscientiousness_01_T1

Distribution

Summary statistics

Value labels

big5consReverseCoded_02_T1

Distribution

Summary statistics

Value labels

big5extraversion_01_T1

Distribution

Summary statistics

Value labels

big5extReverseCoded_02_T1

Distribution

Summary statistics

Value labels

big5neuroticism_01_T1

Distribution

Summary statistics

Value labels

big5neurReverseCoded_02_T1

Distribution

Summary statistics

Value labels

big5openness_01_T1

Distribution

Summary statistics

Value labels

big5openReverseCoded_02_T1

Distribution

Summary statistics

Value labels

fatpct_T1

Distribution

Summary statistics

PA_actplan_01_T1

Distribution

Summary statistics

Value labels

PA_actplan_02_T1

Distribution

Summary statistics

Value labels

PA_actplan_03_T1

Distribution

Summary statistics

Value labels

PA_actplan_04_T1

Distribution

Summary statistics

symptom_T1	padaysLastweek_T1	pafreqUsually_T1	pahrsLastweek_T1
81	83	83	83
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
533	531	531	531

pahrsUsually_T1	paminLastweek_T1	paLastweek_T1	PA_autonomous_T1
83	83	83	87
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
531	531	531	527

PA_identified_T1	PA_actplan_01_T1	PA_actplan_02_T1	PA_actplan_03_T1
91	92	92	92
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
523	522	522	522

PA_actplan_04_T1	PA_copplan_01_T1	PA_copplan_02_T1	PA_copplan_03_T1
92	92	92	92
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
522	522	522	522

PA_copplan_04_T1	PA_dnorm_02_T1	PA_dnorm_01_T1	PA_inorm_01_T1
92	92	92	92
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
522	522	522	522

PA_intention_01_T1	PA_intention_02_T1	PA_controlled_T1	PA_dnorm_T1
92	92	92	92
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
522	522	522	522

PA_inorm_T1	PA_intention_T1	PA_actionplan_T1	PA_copingplan_T1
92	92	92	92
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
522	522	522	522

PA_actCop_T1	PA_integrated_T1	PA_introjected_T1	PA_amotivation_T1
92	92	92	93
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
522	522	522	521

PA_agrbct_01_T1	PA_agrbct_02_T1	PA_agrbct_03_T1	PA_agrbct_04_T1
94	94	94	94
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
520	520	520	520

PA_agrbct_05_T1	PA_agrbct_06_T1	PA_agrbct_07_T1	PA_agrbct_08_T1
94	94	94	94
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
1	1	1	1
0	0	0	0
1	1	1	1
1	1	1	1
520	520	520	520